WO2023179473A1

WO2023179473A1 - Channel feature information reporting method, channel feature information recovery method, terminal and network side device

Info

Publication number: WO2023179473A1
Application number: PCT/CN2023/082127
Authority: WO
Inventors: 任千尧; 孙鹏
Original assignee: 维沃移动通信有限公司
Priority date: 2022-03-21
Filing date: 2023-03-17
Publication date: 2023-09-28
Also published as: CN116827481A

Abstract

The present application relates to the technical field of communications, and discloses a channel feature information reporting method, a channel feature information recovery method, a terminal, and a network side device. The channel feature information reporting method in embodiments of the present application comprises: a terminal processes target channel information into first channel feature information of a first length by using a target AI network model; and the terminal sends second channel feature information to a network side device, the second channel feature information being a portion of content of the first channel feature information.

Description

Channel characteristic information reporting and recovery method, terminal and network side equipment

Cross-references to related applications

This application claims priority from Chinese Patent Application No. 202210283893.X filed in China on March 21, 2022, the entire content of which is incorporated herein by reference.

Technical field

This application belongs to the field of communication technology, and specifically relates to a channel characteristic information reporting and recovery method, terminal and network side equipment.

Background technique

With the application of artificial intelligence (AI) in the communication field, AI network models can be used to encode and decode channel state information (CSI) information.

However, in different channel environments, the degree of compressibility of channel information is different, and the length of information after encoding is also different. For example, simple channel information only requires a short encoding length, but complex channel information requires longer encoding information. . The weight parameters and even network structures of the AI network models corresponding to different lengths of coding information are different. In related technologies, it is necessary to separately train and use the AI network model corresponding to each length of channel information for each length. Encoding and decoding, which results in the need to transmit multiple AI network models between the terminal and the network side device, increasing the transmission overhead of the AI network model.

Contents of the invention

Embodiments of the present application provide a channel characteristic information reporting and recovery method, a terminal and a network side device, so that the terminal can adaptively use the same AI network model for encoding according to the length of the channel information, which can reduce the transmission between the terminal and the network side device. The overhead of AI network models.

In the first aspect, a method for reporting channel characteristic information is provided, which is applied to terminals. The method includes:

The terminal uses the target AI network model to process the target channel information into a first channel of the first length. feature information;

The terminal sends second channel characteristic information to the network side device, where the second channel characteristic information is part of the first channel characteristic information.

In the second aspect, a device for reporting channel characteristic information is provided, which is applied to a terminal. The device includes:

The first processing module is used to process the target channel information into first channel characteristic information of the first length using the target AI network model;

The first sending module is configured to send second channel characteristic information to the network side device, where the second channel characteristic information is part of the first channel characteristic information.

In the third aspect, a channel characteristic information recovery method is provided, which is applied to network side equipment. The method includes:

The network side device receives the second channel characteristic information from the terminal, wherein the second channel characteristic information includes part of the first channel characteristic information, and the first channel characteristic information is the target channel adopted by the terminal using the target AI network model. The first length of channel characteristic information obtained by processing the information;

The network side device uses the first AI network model to process the second channel characteristic information to obtain the target channel information.

In the fourth aspect, a device for recovering channel characteristic information is provided, which is applied to network side equipment. The device includes:

The second receiving module is configured to receive second channel characteristic information from the terminal, wherein the second channel characteristic information includes part of the first channel characteristic information, and the first channel characteristic information is the target AI network adopted by the terminal. The first length of channel characteristic information obtained by processing the target channel information by the model;

The second processing module is configured to use the first AI network model to process the second channel characteristic information to obtain the target channel information.

In a fifth aspect, a terminal is provided. The terminal includes a processor and a memory. The memory stores programs or instructions that can be run on the processor. When the program or instructions are executed by the processor, the following implementations are implemented: The steps of the method described in one aspect.

In a sixth aspect, a terminal is provided, including a processor and a communication interface, wherein the processing The processor is used to process the target channel information into first channel characteristic information of a first length using the target AI network model, and the communication interface is used to send the second channel characteristic information to the network side device, and the second channel characteristic information is the first channel characteristic information. part of the message.

In a seventh aspect, a network side device is provided. The network side device includes a processor and a memory. The memory stores programs or instructions that can be run on the processor. The program or instructions are executed by the processor. When implementing the steps of the method described in the first aspect.

In an eighth aspect, a network side device is provided, including a processor and a communication interface, wherein the communication interface is used to receive second channel characteristic information from a terminal, and the second channel characteristic information includes the first channel characteristic information. part, the first channel characteristic information is the first length of channel characteristic information obtained by the terminal using the target AI network model to process the target channel information; the processor is configured to use the first AI network model to process the third The two channel characteristic information are processed to obtain the target channel information.

A ninth aspect provides a communication system, including: a terminal and a network side device. The terminal can be configured to perform the steps of the channel characteristic information reporting method described in the first aspect. The network side device can be configured to perform the steps of the channel characteristic information reporting method as described in the first aspect. The steps of the channel characteristic information recovery method described in the three aspects.

In a tenth aspect, a readable storage medium is provided. Programs or instructions are stored on the readable storage medium. When the programs or instructions are executed by a processor, the steps of the method described in the first aspect are implemented, or the steps of the method are implemented as described in the first aspect. The steps of the method described in the third aspect.

In an eleventh aspect, a chip is provided. The chip includes a processor and a communication interface. The communication interface is coupled to the processor. The processor is used to run programs or instructions to implement the method described in the first aspect. method, or implement a method as described in the third aspect.

In a twelfth aspect, a computer program/program product is provided, the computer program/program product is stored in a storage medium, and the computer program/program product is executed by at least one processor to implement the first aspect or the second aspect. The steps of the method described in three aspects.

In this embodiment of the present application, the terminal uses the target AI network model to process the target channel information into the first channel characteristic information of the first length; the terminal sends the second channel characteristic information to the network side device, and the second channel characteristic information is the first channel characteristic information. Part of the channel characteristic information. In this way, in different channel environments, the terminal can adaptively use the same AI network model for encoding according to the length of the channel information, and only report part of the channel characteristic information of the corresponding length to the network side device, so that the network side can adopt pre-set The configured AI network model corresponding to the length is used to decode this part of the channel characteristic information, and can reduce the overhead of transmitting the AI network model between the terminal and the network side device.

Description of the drawings

Figure 1 is a schematic structural diagram of a wireless communication system to which embodiments of the present application can be applied;

Figure 2 is a flow chart of a method for reporting channel characteristic information provided by an embodiment of the present application;

Figure 3 is a schematic diagram of the architecture of the neural network model;

Figure 4 is a schematic diagram of a neuron;

Figure 5 is a schematic diagram of the power spectrum of the delay path in the embodiment of the present application;

Figure 6 is a flow chart of a method for recovering channel characteristic information provided by an embodiment of the present application;

Figure 7a is one of the schematic diagrams of the corresponding relationship between the decoder and the channel characteristic information in the embodiment of the present application;

Figure 7b is the second schematic diagram of the corresponding relationship between the decoder and the channel characteristic information in the embodiment of the present application;

Figure 8 is a schematic structural diagram of a device for reporting channel characteristic information provided by an embodiment of the present application;

Figure 9 is a schematic structural diagram of a device for recovering channel characteristic information provided by an embodiment of the present application;

Figure 10 is a schematic structural diagram of a communication device provided by an embodiment of the present application;

Figure 11 is a schematic structural diagram of a terminal provided by an embodiment of the present application;

Figure 12 is a schematic structural diagram of a network side device provided by an embodiment of the present application.

Detailed ways

The technical solutions in the embodiments of the present application will be clearly described below with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, but not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by those of ordinary skill in the art fall within the scope of protection of this application.

The terms "first", "second", etc. in the description and claims of this application are used to distinguish similar objects and are not used to describe a specific order or sequence. It is to be understood that the terms so used are interchangeable under appropriate circumstances so that the embodiments of the present application can be practiced in sequences other than those illustrated or described herein, and that "first" and "second" are distinguished objects It is usually one type, and the number of objects is not limited. For example, the first object can be one or multiple. In addition, "and/or" in the description and claims indicates at least one of the connected objects, and the character "/" generally indicates that the related objects are in an "or" relationship.

It is worth pointing out that the technology described in the embodiments of this application is not limited to Long Term Evolution (LTE)/LTE Evolution (LTE-Advanced, LTE-A) systems, and can also be used in other wireless communication systems, such as code Code Division Multiple Access (CDMA), Time Division Multiple Access (Time Division Multiple Access, TDMA), Frequency Division Multiple Access (Frequency Division Multiple Access, FDMA), Orthogonal Frequency Division Multiple Access (OFDMA), Single-carrier Frequency Division Multiple Access (SC-FDMA) ) and other systems. The terms "system" and "network" in the embodiments of this application are often used interchangeably, and the described technology can be used not only for the above-mentioned systems and radio technologies, but also for other systems and radio technologies. The following description describes a New Radio (NR) system for example purposes, and NR terminology is used in much of the following description, but these techniques can also be applied to applications other than NR system applications, such as 6th ^generation Generation, 6G) communication system.

Figure 1 shows a block diagram of a wireless communication system to which embodiments of the present application are applicable. The wireless communication system includes a terminal 11 and a network side device 12. Among them, the terminal 11 can be a mobile phone, a tablet computer (Tablet Personal Computer), a laptop computer (Laptop Computer), or a notebook computer, a personal digital assistant (Personal Digital Assistant, PDA), a handheld computer, a netbook, or a super mobile personal computer. (ultra-mobile personal computer, UMPC), mobile Internet device (Mobile Internet Device, MID), augmented reality (augmented reality, AR)/virtual reality (VR) equipment, robots, wearable devices (Wearable Device) , vehicle user equipment (VUE), pedestrian terminal (Pedestrian User Equipment, PUE), smart home (home equipment with wireless communication functions, such as refrigerators, TVs, washing machines or furniture, etc.), game consoles, personal computers (personal computer, PC), teller machine or self-service machine and other terminal-side devices. Wearable devices include: smart watches, smart bracelets, smart headphones, smart glasses, smart jewelry (smart bracelets, smart bracelets, smart rings, smart necklaces, smart anklets) bracelets, smart anklets, etc.), smart wristbands, smart clothing, etc. It should be noted that the embodiment of the present application does not limit the specific type of the terminal 11. The network side equipment 12 may include access network equipment or core network equipment, where the access network equipment may also be called wireless access network equipment, radio access network (Radio Access Network, RAN), radio access network function or wireless access network unit. Access network equipment can include base stations, Wireless Local Area Network (WLAN) access points or WiFi nodes, etc. The base station can be called Node B, Evolved Node B (eNB), access point, base transceiver station ( Base Transceiver Station (BTS), radio base station, radio transceiver, Basic Service Set (BSS), Extended Service Set (ESS), home B-node, home evolved B-node, sending and receiving point ( Transmitting Receiving Point (TRP) or some other suitable term in the field, as long as the same technical effect is achieved, the base station is not limited to specific technical terms. It should be noted that in the embodiment of this application, only the NR system is used The base station is introduced as an example, and the specific type of base station is not limited.

In wireless communication technology, accurate CSI feedback is crucial to channel capacity. Especially for multi-antenna systems, the transmitter can optimize signal transmission based on CSI to better match the channel status. For example: Channel Quality Indicator (CQI) can be used to select the appropriate Modulation and Coding Scheme (MCS) to achieve link adaptation; Precoding Matrix Indicator (PMI) can be used To achieve eigen beamforming (eigen beamforming), thereby maximizing the strength of the received signal, or to suppress interference (such as inter-cell interference, interference between multiple users, etc.). Therefore, since multi-antenna technology (such as Multi-Input Multi-Output (MIMO)) was proposed, the acquisition of CSI has always been a research hotspot.

Usually, the network side device sends CSI reference signals (CSI-Reference Signals, CSI-RS) on certain time-frequency resources of a certain time slot (slot). The terminal performs channel estimation based on the CSI-RS and calculates the channel on this slot. Information, the PMI is fed back to the base station through the codebook. The network side device combines the channel information based on the codebook information fed back by the terminal. Before the terminal reports the CSI next time, the network side device uses this channel information to perform data precoding and multi-user scheduling. .

In order to further reduce CSI feedback overhead, the terminal can change the PMI reported on each subband to report PMI according to the delay (delay domain, that is, frequency domain). Since the channels in the delay domain are more concentrated, PMI with less delay can be approximated The PMI of all subbands can be regarded as reporting after compressing the delay field information.

Similarly, in order to reduce overhead, the network side device can precode the CSI-RS in advance and send the coded CSI-RS to the terminal. What the terminal sees is the channel corresponding to the coded CSI-RS. The terminal only needs to Just select several stronger ports from the ports indicated by the network-side device and report the coefficients corresponding to these ports.

In related technologies, the use of AI network models to compress channel information can improve the compression effect of channel feature information. Among them, AI network models have many implementation methods, such as: neural networks, decision trees, support vector machines, and Bayesian Classifier etc. For ease of explanation, in the embodiment of the present application, the AI network model is a neural network as an example, but the specific type of the AI network model is not limited.

In the embodiment of the present application, the target AI network model with encoding function (that is, the AI network model in the encoder, which can also be called the encoder network model or the encoding AI network model) is used to compress and encode the channel information at the terminal. And report the encoded channel characteristic information to the network side device (for example: base station). On the base station side, the first AI network model with decoding function (that is, the AI network model in the decoder, which can also be called decoding The decoder network model or decoding AI network model) decodes the compressed channel characteristic information to restore the channel information. At this time, the first AI network model of the base station and the target AI network model of the terminal need to be jointly trained to achieve a reasonable matching degree. The neural network forms a joint neural network through the encoder network model of the terminal and the decoder network model of the base station, and is jointly trained by the network side device. After the training is completed, the base station sends the encoder network model to the terminal.

The terminal estimates the CSI Reference Signal (CSI-RS) and performs calculations based on the estimated channel information to obtain the calculated channel information; then, the calculated channel information or the original estimated channel information is passed through the coding network model Encoding is performed, the encoding result is obtained, and finally the encoding result is sent to the base station. On the base station side, after receiving the encoded result, the base station inputs it into the decoding network model and uses the decoding network model to restore the channel information.

However, under different channel environments, the degree of compressibility of channel information is different. Therefore, the length of the channel information after encoding is also different. For example, simple channel information only requires a short encoding length, but complex channel information requires a longer length. encoded information. In this way, the weight parameters and even the network structure of the AI network model corresponding to the encoding information of different lengths are different, which requires retraining the AI network model that matches the encoding length. It can be seen that in related technologies, it is necessary to separately train and use the AI network model corresponding to the length of the channel information for each length to encode and decode. This results in the need to transmit multiple data between the terminal and the network side device. An AI network model increases the transmission overhead of the AI network model and the network side device trains and uses it separately for each length of channel information. When encoding and decoding the AI network model corresponding to this length, the calculation amount of the network side device is increased.

In the embodiment of this application, the terminal can use the target AI network model to process the channel information into fixed-length coded information (i.e., first channel characteristic information), and report part of the first channel characteristic information to the network side device. In this way, The terminal may select the second length of the second channel characteristic information to report according to the instructions of the network side device and/or the terminal independently selects the second length of the second channel characteristic information to report to the network side device. In this way, The terminal only needs to use one encoding network to encode the channel information, and the network side device only needs to use the decoding network corresponding to the second length to decode part of the channel characteristic information of the second length.

It should be noted that in the implementation, the above-mentioned terminal reports the second channel characteristic information to the network side device, and may use the CSI reporting method to carry the second channel characteristic information in the CSI report to report to the network side device, where, The channel characteristic information may specifically be PMI information. Of course, the above-mentioned second channel characteristic information can also be reported to the network side device in any other manner. For the convenience of explanation, in the embodiment of this application, the reporting of the second channel characteristic information in the form of CSI reporting is used as an example for illustration. Does not constitute a specific limitation.

In addition, the first length and the second length in the embodiment of the present application may be the number of bits of the corresponding channel characteristic information after quantization, or the number of coefficients included in the corresponding channel characteristic information before quantization. For ease of explanation, in the embodiment of the present application, the first length and the second length are respectively the number of bits, as an example, and no specific limitation is constituted here.

Below in conjunction with the accompanying drawings, the channel characteristic information reporting method, channel characteristic information recovery method, channel characteristic information reporting device, channel characteristic information recovery device and communication equipment provided by the embodiments of the present application will be described in detail through some embodiments and application scenarios. .

Referring to Figure 2, an embodiment of the present application provides a method for reporting channel characteristic information. The execution subject may be a terminal. The terminal may be various types of terminals 11 listed in Figure 1, or other than those shown in Figure 1. Terminals other than the terminal types listed in the embodiment are not specifically limited here. As shown in Figure 2, the channel characteristic information reporting method may include the following steps:

Step 201: The terminal uses the target AI network model to process the target channel information into first channel characteristic information of a first length.

In implementation, the above target AI network model may include multiple types of AI algorithm modules, such as neural networks, decision trees, support vector machines, Bayesian classifiers, etc., which are not specifically limited here, and for ease of explanation, the following In the embodiment, the AI algorithm model is a neural network model as an example for illustration, which does not constitute a specific limitation.

As shown in Figure 3, the neural network model includes an input layer, a hidden layer and an output layer, which can predict possible output results (Y) based on the entry and exit information (X ₁ ~ X _n ) obtained by the input layer. The neural network model consists of a large number of neurons, as shown in Figure 4. The parameters of the neurons include: input parameters a ₁ ~ a _K , weight w, bias b and activation function σ(z), and the parameters obtained with these parameters Output value a, among which, common activation functions include Sigmoid function, hyperbolic tangent (tanh) function, linear rectified function (Rectified Linear Unit, ReLU, also called modified linear unit) function, etc. , and z in the above function σ(z) can be calculated by the following formula:
z＝a ₁ w ₁ +…+a _k w _k +a _K w _K +b

Among them, K represents the total number of input parameters.

The parameters of the neural network are optimized through optimization algorithms. An optimization algorithm is a type of algorithm that can help us minimize or maximize an objective function (sometimes also called a loss function). The objective function is often a mathematical combination of model parameters and data. For example, given the data The difference (f(x)-Y) between it and the true value is the loss function. Our purpose is to find appropriate W and b to minimize the value of the above loss function. The smaller the loss value, the closer our model is to the real situation.

Currently, common optimization algorithms are basically based on error back propagation algorithm. The basic idea of the error back propagation algorithm is that the learning process consists of two processes: forward propagation of signals and back propagation of errors. During forward propagation, the input sample is passed in from the input layer, processed layer by layer by each hidden layer, and then transmitted to the output layer. If the actual output of the output layer does not match the expected output, it will enter the error backpropagation stage. Error backpropagation is to backpropagate the output error in some form to the input layer layer by layer through the hidden layer, and allocate the error to all units in each layer, thereby obtaining the error signal of each layer unit. This error signal is used as a correction for each unit. The basis for the weight. This process of adjusting the weights of each layer in forward signal propagation and error back propagation is carried out over and over again. The process of continuous adjustment of weights is the learning and training process of the network. This process continues until the error of the network output is reduced to an acceptable level, or until a preset number of learning times.

Common optimization algorithms include gradient descent (Gradient Descent), stochastic gradient descent (Stochastic Gradient Descent, SGD), mini-batch gradient descent (mini-batch gradient descent), momentum method (Momentum), Nesterov (which represents stochastic gradient with momentum). descent), adaptive gradient descent (Adaptive gradient descent, Adagrad), adaptive learning rate adjustment (Adadelta), root mean square error reduction (root mean square prop, RMSprop), adaptive momentum estimation (Adaptive Moment Estimation, Adam) wait.

When these optimization algorithms perform error backpropagation, they calculate the derivative/partial derivative of the current neuron based on the error/loss obtained by the loss function, plus the influence of the learning rate, previous gradient/derivative/partial derivative, etc., to obtain the gradient. Pass the gradient to the previous layer.

In implementation, the target AI network model can be used to encode channel information, which can Channel information under different channel environments is encoded into first channel characteristic information of fixed length (ie, first length). In implementation, the above-mentioned first length may be a longer length. When the encoding result of the channel information in a certain channel environment is shorter than the first length, any method such as zero padding or redundant coding can be used to supplement the encoding result of the channel information in the channel environment to the first length.

Optionally, before the terminal uses the target AI network model to process the target channel information into the first channel characteristic information of the first length, the method further includes:

The terminal performs channel estimation on the channel state information - reference signal CSI-RS or tracking reference signal (Tracking Reference Signal, TRS) to obtain the target channel information; or,

The terminal preprocesses the channel information obtained by channel estimation to obtain the target channel information.

In this embodiment, the target channel information encoded using the target AI network model may be the channel information obtained by the terminal estimating the CSI-RS channel or the TRS channel, or the terminal performs certain preprocessing on the estimated channel information. The obtained channel information is not specifically limited here.

Step 202: The terminal sends second channel characteristic information to the network side device, where the second channel characteristic information is part of the first channel characteristic information.

In an implementation, the second channel characteristic information may be a part of the first channel characteristic information: the terminal intercepts part of the first channel characteristic information as the second channel characteristic information.

In the implementation, the terminal may send the second bit of the second channel characteristic information to the network side device; or, the terminal may also report the channel characteristic information M times and send M pieces of second channel characteristic information of different lengths or different contents to the network side device. Channel characteristic information, that is, in each channel characteristic information reporting process, a piece of second channel characteristic information is reported, but the second channel characteristic information reported through different channel characteristic information reporting processes has different lengths or different contents.

The terminal sends second channel characteristic information to the network side device, including:

The terminal sends a second length of second channel characteristic information intercepted from the first channel characteristic information to the network side device, and the second length is less than or equal to the first length.

In this embodiment, the terminal only reports the second channel characteristic information to the network side device, and the length of the second channel characteristic information may be the second length.

In an implementation, the second length may be determined according to instructions from the network side device, and/or the terminal determines which second length to adopt. Correspondingly, when the network side device receives the second channel characteristic information of the second length, the first AI network model corresponding to the second length can be used to decode the second channel characteristic information, thereby recovering the channel information.

It should be noted that during the wireless communication process, the terminal can report channel characteristic information respectively at different time domain positions, and the second length corresponding to each channel characteristic information report can be the same or different, which is not specifically limited here. For example, the first channel characteristic information of the first length may be divided into K channel characteristic information segments, and the second channel characteristic information of the second length may include 1 to K channel characteristic information segments.

In a possible implementation, when receiving the second channel characteristic information currently reported by the terminal, the network side device can input the second channel characteristic information into the first AI network model, so as to use the first AI network model to The second channel characteristic information is processed to restore the channel information.

In another possible implementation, the network side device can store the historical channel characteristic information reported by the terminal within the historical time, and when receiving the second channel characteristic information currently reported by the terminal, it can update based on the second channel characteristic information. historical channel characteristic information, and then use the first AI network model to process the updated historical channel characteristic information to obtain the target channel information. For example: Assume that the terminal reports channel characteristic information cyclically in the order of the second length being N0, N1..., then when the network side device receives the second channel characteristic information of length N0 for the first time, based on the length of N0 The second channel characteristic information of length N1 is used to perform channel recovery; then, when the network side device receives the second channel characteristic information of length N1, it performs channel recovery based on the second channel characteristic information of length N0 and the second channel characteristic information of length N1. Channel restored. In addition, during the next cycle, when the network side device receives the second channel characteristic information of length N0, it replaces the second channel characteristic information of length N0 in the historical channel characteristic information based on the second channel characteristic information of length N0. Channel characteristic information, and use the updated historical channel characteristic information for channel recovery.

For another example: the terminal reports the second channel characteristic information with a length of N0 for the first time, then reports the second channel characteristic information with a length of N1-N0 next time, and then reports the second channel characteristic information with a length of N2-N1 next time. And cycle in sequence; after receiving the second channel characteristic information, the base station uses all the second channel characteristic information for decoding, that is, when there is only the second channel characteristic information of length N0, the second channel characteristic information of length N0 is used; if there are N0 and When the second channel characteristic information of length N1-N0 is provided, The second channel characteristic information of length N1 is combined based on the second channel characteristic information of length N0 and N1-N0, and is decoded based on the second channel characteristic information of length N1, and iterates in sequence until the third channel characteristic information of length L is combined. 1. Channel characteristic information. In the next cycle, the length L is still used for decoding, and the channel characteristic information corresponding to N0 in the historical channel characteristic information is replaced with the new N0, and the iteration is updated accordingly.

In practical applications, the target AI network model and the first AI network model can be jointly trained by network-side devices, and one target AI network model can correspond to at least one first AI network model, where each first AI network model have respective corresponding lengths, so that after the second length is determined, the first AI network model corresponding to the second length can be used to decode the second channel characteristic information to achieve channel recovery.

Optionally, the second length of second channel characteristic information includes at least one of the following:

For the first N bits or coefficients in the first channel characteristic information, N is equal to the number of bits corresponding to the second length or the number of coefficients corresponding to the second length;

N bits or coefficients in the first channel characteristic information whose importance level is greater than the preset level;

N bits or coefficients in the first channel characteristic information other than the reported channel characteristic information.

Option 1: In the case where the second channel characteristic information of the second length includes the first N bits or coefficients in the first channel characteristic information, the terminal directly follows the order of each bit in the first channel characteristic information. To report N bits or coefficients of the second channel characteristic information. For example, assuming that N is equal to 100 bits, the first 100 bits of the first channel characteristic information are reported.

Option 2: In the case where the second channel characteristic information of the second length includes N bits or coefficients in the first channel characteristic information whose importance level is greater than a preset level, the N bits or coefficients in the first channel characteristic information may be modified. Each bit or each bit interval or coefficient included is divided into importance levels. In this way, the terminal can preferentially report N bits or coefficients with higher importance levels in the first channel characteristic information to the network side device.

Option three: In the case where the second channel characteristic information of the second length includes N bits or coefficients in the first channel characteristic information in addition to the reported second channel characteristic information, it is the same as option one. The difference is that when the terminal reports channel characteristic information multiple times, the reporting method of option three can avoid repeated reporting of channel characteristic information. For example: the terminal performs two messages Channel characteristic information is reported. The second length corresponding to the first channel characteristic information report is equal to 100 bits, and the second length corresponding to the second channel characteristic information report is equal to 200 bits. When option one is adopted, the terminal can report bits 0 to 99 of the first channel characteristic information for the first time, and bits 0 to 199 of the first channel characteristic information for the second time; and when option three is adopted, the terminal can report bits 0 to 99 of the first channel characteristic information for the second time. The 0th to 99th bits in the first channel characteristic information can be reported, and the second time can report the other 200 bits after the 100th bit in the first channel characteristic information.

It should be noted that in implementation, at least two of the above options one to three can be combined. For example: when the second channel characteristic information of the second length includes option one and option three, the terminal first The second channel characteristic information reported for the second time may be bits 0 to (N0-1) in the first channel characteristic information, and the second channel characteristic information reported for the second time may be bits 0 to (N0) in the first channel characteristic information. -1) part and N1-N0 length in N0-(L-1), where L represents the first length, N0 represents the second length used in the first report, and N1 represents the second length used in the second report . In the implementation, the second channel characteristic information reported for the second time may include the bit content reported for the first time, and may also include additional N1-N0 length content, and the 0~(N0-1) part and N0-(L The length of N1-N0 in -1) may be two segments of channel characteristic information bits that are continuous or discontinuous.

In implementation, the above-mentioned second length may be indicated by the network side device or the second length may be determined by the terminal according to conditions agreed upon in the protocol.

As an optional implementation, before the terminal sends the second channel characteristic information of the second length intercepted from the first channel characteristic information to the network side device, the method further includes:

The terminal receives first indication information from the network side device, wherein the first indication information indicates the second length and/or a first encoding identifier, and the first encoding identifier and the second length association.

In implementation, the above-mentioned first encoding identifier can be understood as identification information of the encoding length corresponding to the first AI network model. In this way, based on the first coding identifier, it can be determined how much coding length of second channel characteristic information the terminal needs to report. For example: a target AI network model corresponds to K first AI network models, the inputs of the K first AI network models are part or all of the channel feature information output by the target AI network model, and the input length of the K first AI network models are N1, N2 to NK respectively, then the above-mentioned first encoding identifier may be i or i-1 in Ni. In implementation, the input length of the K first AI network models may be agreed upon by the protocol, and both the network side device and the terminal know the K first AI network models. In this way, when the network side device indicates a coding identifier to the terminal, the terminal can determine the second length to be reported based on the coding identifier, so that in the first channel characteristic information whose coded length is the first length Intercept a part with length Ni, where i is the first encoding identifier indicated by the network side device.

Among them, the above-mentioned first indication information is configured by high-level signaling, for example: through Radio Resource Control (Radio Resource Control, RRC) signaling or Media Access Control (Medium Access Control, MAC) Control Element (Control Element, CE), etc. Configure the second length, so that the terminal can report the second channel characteristic information of the same length in each channel characteristic information report.

Of course, when the second channel characteristic information is carried in the channel state information CSI report, the above-mentioned first indication information can also be the indication information in the CSI report configuration (CSI report config), or the network side device can configure each length corresponding to a CSI resource (resource), then the second length indicated by the first indication information can be understood as the length corresponding to the CSI resource used by the terminal, and the first indication information is not specifically limited here.

In this embodiment, the network side device may indicate the second length to the terminal, so that the terminal intercepts the second channel characteristic information of the corresponding length from the first channel characteristic information according to the instruction of the network side device, and reports it to the network side device.

As another optional implementation, before the terminal sends the second channel characteristic information of the second length intercepted from the first channel characteristic information to the network side device, the method further includes:

The terminal determines the second length according to at least one of channel characteristics and channel conditions corresponding to the target channel information.

In an implementation, the above-mentioned terminal determines the second length according to at least one of channel characteristics and channel conditions corresponding to the target channel information. The terminal may determine the channel characteristics of the target channel according to the target channel information, thereby determining the channel. The second length corresponding to the characteristic; and/or the terminal can determine whether the channel quality of the target channel satisfies the preset channel conditions according to the target channel information, and thereby determine the corresponding second length based on the judgment result.

In this embodiment, the difference from the embodiment in which the network side device indicates the second length to the terminal is that the terminal can determine the second length according to the target channel information, thereby reporting the second channel characteristics of the second length to the network side device. information.

In an optional implementation, the terminal determines the channel corresponding to the target channel information. Characteristics that determine the second length include:

The terminal determines that the length of the value association of the target channel parameter of the target channel corresponding to the target channel information is the second length according to the first association relationship, wherein the first association relationship includes the value of the target channel parameter. The relationship between each value or each value range and length; or,

The terminal determines that the length corresponding to the encoding identifier associated with the value of the target channel parameter of the target channel corresponding to the target channel information is the second length according to the second association relationship, wherein the second association relationship includes the The correlation between each value or each value range of the target channel parameter and the coding identifier.

In an implementation, corresponding to the above-mentioned first indication information that may indicate the second length or the first coding identifier corresponding to the second length, the terminal may also determine based on the correlation between the value of the channel parameter and the length or coding identifier. The second length of the target channel parameter association.

Wherein, the target channel parameters of the target channel may include at least one of the following:

The target channel is Line of Sight (LOS) propagation or Non-Line of Sight (NLOS) propagation;

The number of effective delay paths of the target channel;

The delay interval between the two target paths of the target channel;

The number of effective beams of the target channel. The effective beams include beams corresponding to the orthogonal basis of Discrete Fourier Transform (DFT) whose power is greater than the first threshold.

Option one, when the target channel is line-of-sight propagation, the channel quality is better than that of non-line-of-sight propagation. Shorter second channel characteristic information can be reported when the target channel is line-of-sight propagation, and when the target channel is line-of-sight propagation, the channel quality is better. When the channel is non-line-of-sight propagation, longer second channel characteristic information is reported. For example: assuming K=2, LOS uses N0, NLOS uses N1, N0<N1, especially, N1=L, where K represents the second length The number of values, L represents the first length;

Option two, the greater the number of effective delay paths of the target channel, the longer the reported second channel characteristic information can be, where the effective delay paths include at least one of the following: the corresponding power or amplitude is greater than the first The delay path of the threshold value, the corresponding delay path of the maximum power or amplitude. For example: In the power diagram shown in Figure 5, assuming that the effective delay paths include delay paths with power or amplitude greater than the first threshold, the effective delay paths are respectively located in the delay domain positions: -2, 0, 1, 4 four paths at; assuming effective delay path Including delay paths with maximum power or amplitude, the effective delay paths are three paths located at -2, 0, and 4 in the delay domain.

Option 3: The greater the delay distance between the two target paths of the target channel, the longer the reported second channel characteristic information can be. Among them, the two target paths can be any two paths of the target channel, for example: paths corresponding to two maximum values. The time delay spacing of the two target paths can reflect the path included in the target signal in the frequency domain. Concentrated intensity.

Option 4: The greater the number of effective beams of the target channel, the longer the reported second channel characteristic information can be.

In this embodiment, the terminal can determine the second length according to the value of the detected target channel parameter of the target channel, so that the reported second channel characteristic information of the second length matches the channel state of the target channel.

In another optional implementation, the method further includes:

The terminal receives relevant information of K first AI network models from the network side device, wherein the K first AI network models correspond to the target AI network model, and the K first AI network models The models are respectively used to decode the channel characteristic information of their corresponding lengths;

The terminal determines the second length according to channel conditions, including:

The terminal intercepts K pieces of second channel characteristic information from the first channel characteristic information, and processes the second channel characteristic information of corresponding lengths into first K pieces of first AI network models respectively. channel information;

The terminal obtains the degree of matching between the K pieces of the first channel information and the target channel information respectively;

When the terminal determines that the matching degree between the target first channel information and the target channel information satisfies a preset condition, the terminal determines that the second length is equal to the first AI network used to process the target first channel information. The length corresponding to the model, wherein the K pieces of first channel information obtained by processing the K pieces of the first AI network models include the target first channel information.

In implementation, the relevant information of the first AI network model may be model parameters, model configuration, model identification information, etc., and the terminal can determine which first AI network model the network side device will use to decode the second AI network model based on the relevant information. Channel characteristic information. Then, the terminal can use the first AI network model or a simplified network model of the first AI network model to simulate the network-side device corresponding to the long-term degree of decoding of the second channel characteristic information, thereby comparing the simulated decoding result (ie, the first channel information) with the target channel information to determine the degree of matching between the two.

Among them, the higher the matching degree between the first channel information and the target channel information, it means that the first AI network model adopted can restore the target channel information more accurately. In practical applications, the matching degree between the above-mentioned target first channel information and the target channel information satisfies the preset conditions, which can be understood as: obtaining the second channel corresponding to the length of the first AI network model of the target first channel information. The decoding result of the characteristic information can meet business requirements or communication quality requirements.

Optionally, the terminal device may traverse each first AI network model to determine whether the decoding result of each first AI network model for the corresponding length of the second channel characteristic information matches the target channel information to a satisfactory degree. Preset conditions. In implementation, there may be a situation where the degree of matching between the first channel information obtained by at least two first AI network models and the target channel information satisfies the preset conditions. In this case, it is possible to further select from the at least two first AI network models. The smallest one of the corresponding lengths of the two first AI network models is selected as the second length, thereby intercepting the second channel characteristic information of the second length from the first channel characteristic information, and reporting it to the network side device.

Of course, the terminal device can also sequentially determine the degree of matching between the decoding result of the second channel characteristic information of the corresponding length of the first AI network model pair and the target channel information, and determine the length of the corresponding length of a certain first AI network model pair. When the matching degree between the decoding result of the second channel characteristic information and the target channel information satisfies the preset conditions, the second length is determined to be the length corresponding to the first AI network model pair. In this way, the determination of the second length can be reduced. amount of calculation.

Optionally, the degree of matching between the target first channel information and the target channel information satisfies a preset condition including at least one of the following:

The correlation between the target first channel information and the target channel information is greater than or equal to a preset correlation;

The channel capacity of the target first channel information is greater than or equal to a first preset value times the channel capacity of the target channel information, and the first preset value is greater than 0 and less than or equal to 1;

The target first channel information is the one in which a channel quality indicator (Channel quality indicator, CQI) among the K pieces of first channel information is the same as or closest to the CQI of the target channel information;

The target first channel information is modulated and coded among the K pieces of first channel information. The scheme (Modulation and coding scheme, MCS) is the same as or the closest one to the MCS of the target channel information.

In implementation, the correlation between the above-mentioned target first channel information and the target channel information may be the similarity between the information content of the target first channel information and the target channel information, for example: the target first channel information and the above-mentioned target channel information. Mutual information between target channel information.

In addition, the second channel characteristic information may only include part of the first channel characteristic information, and the above-mentioned first channel information may only include part of the information in the target channel information, then the second channel characteristics based on different lengths and/or different positions The channel information decoded by the information may contain different channel capacities, CQIs, MCSs, etc. In this case, it may be preferable to select the channel capacity of the first channel information to be greater than the first preset value times the channel capacity of the target channel information. The length of the first AI network model is used as the second length, where the first preset value may be a value indicated by the network side device or agreed upon by the protocol. When the channel capacity meets the first preset value, the second length The second channel characteristic information can decode channel information that meets business requirements and/or channel quality requirements. In addition, the first channel information that is closest to the CQI and/or MCS in the target channel information may also be used as the target first channel information.

Optionally, the channel characteristic information reporting method further includes:

The terminal sends second indication information to the network side device, and the second indication information indicates the second length.

In this embodiment, when determining the second length, the terminal also reports the second length to the network side device, so that the network side device directly uses the first AI network model corresponding to the second length to decode the second channel characteristic information. .

It should be noted that in implementation, after the terminal determines the second length, the terminal may not report the second length to the network side device. In this case, the network side device may detect the length of the second channel characteristic information reported by the terminal. Therefore, the first AI network model corresponding to the length is used to decode the second channel characteristic information, which is not specifically limited here.

In an implementation, the CSI report may include a fixed-length CSI part (eg, CSI Part1) and a variable-length CSI part (eg, CSI Part2). At this time, the above-mentioned second indication information may be carried in a fixed-length CSI part or a variable-length CSI part in the CSI report.

In addition, the second channel characteristic information of the second length may also be located in the variable length CSI part, Alternatively, one part is in the fixed-length CSI part and the other part is in the variable-length CSI part.

Specifically, given that the value range of the second length may include multiple values between the minimum length and the first length, and the fixed-length CSI part in the CSI report often only accommodates smaller lengths, at this time, the The minimum length part of the second channel characteristic information of the second length is placed in the fixed-length CSI part of the CSI report, and the other parts of the second channel characteristic information are placed in the variable-length CSI part of the CSI report. In implementation, the above-mentioned minimum length may be less than or equal to the second length, that is, the minimum length may be equal to the minimum value that the second length may take. For example, assume that the input lengths of the K first AI network models are from short to For long arrays N1~NK, the minimum length can be equal to N1. In the implementation, N2 to NK all contain the channel characteristic information corresponding to N1, so that the fixed-length CSI part in the CSI report can fixedly carry the content of the 0th to (N1-1) bits in the first channel characteristic information. And when the second length is greater than N1, the content located after the (N1-1)th bit in the second channel characteristic information may be placed in the variable-length CSI part of the CSI report.

Of course, the above examples are only examples. In practical applications, the position of the minimum length part of the second channel characteristic information of the second length in the second channel characteristic information can be agreed by the protocol, for example: the second channel characteristic information The minimum length portion of may include at least one of the following:

The first X bits in the second channel characteristic information, X is equal to the minimum length;

X bits in the second channel characteristic information whose importance level is greater than a preset level.

For example, the second indication information is carried in a fixed-length CSI part in the CSI report, and the second channel characteristic information of the second length is carried in a variable-length CSI part in the CSI report.

Example 2: The minimum length part of the second channel characteristic information of the second length and the second indication information are carried in the fixed length CSI part of the CSI report, and the second channel characteristic information of the second length The variable length part in , except the minimum length part, is carried in the variable length CSI part in the CSI report.

In example three, the second indication information and the second channel characteristic information of the second length are both carried in a variable-length CSI part in the CSI report.

In the M times of channel feature information reporting, the terminal sends the second channel feature information intercepted from the first channel feature information to the network side device respectively, where M is an integer greater than 1, and the M times channel feature information The lengths of the second channel characteristic information reported by the information are different from each other, or the contents of the second channel characteristic information reported by the M times of channel characteristic information are different from each other.

In implementation, the above-mentioned M pieces of second channel characteristic information can be divided into M times of reporting, that is, the terminal reports M times of channel characteristic information, each time reporting a piece of second channel characteristic information. Of course, in actual applications, the terminal may also report at least two second channel characteristic information at one time, which is not specifically limited here.

For example, the terminal may send the second channel characteristic information intercepted from the first channel characteristic information to the network side device in turn in order of length from small to large in M times of channel characteristic information reporting. In this way, the network side device can gradually improve the accuracy of channel recovery during the process of channel recovery based on the received second channel characteristic information.

For another example: in the M times of channel characteristic information reporting, the terminal can determine the corresponding second lengths of the M times of channel characteristic information reporting according to the current channel environment. At this time, the second length of the M pieces of second channel characteristic information is It can be the same or different. In this way, after a period of time, the network side device may obtain M pieces of second channel characteristic information with different lengths (that is, the historical channel characteristic information includes M pieces of mutually different lengths reported by the terminal in the historical time period). Different second channel characteristic information), in this way, during the subsequent channel recovery process, the network side device can update the historical channel characteristic information based on the second channel characteristic information currently reported by the terminal, and use all updated historical channel characteristics information to perform channel recovery. That is to say, the length of all the historical channel characteristic information can be the same as the length of the first channel characteristic information. However, part of the historical channel characteristic information is the current channel characteristic information, and the other part is the channel once reported by the terminal. Feature information.

Optionally, in the case where the second channel characteristic is carried in the CSI report, the time-frequency resource location for the M times of channel characteristic information reporting is configured by a piece of CSI report configuration information;

or,

The time-frequency resource locations for the M channel characteristic information reports are configured by M pieces of CSI report configuration information.

In an optional implementation manner, the time-frequency resource locations for the M times of channel characteristic information reporting can be configured in the same CSI report configuration information (CSI report config), that is, one CSI report config configures M time-frequency resource locations for reporting channel characteristic information, and the terminal reports second channel characteristic information at each time-frequency resource location.

In this way, the configuration process of time-frequency resource locations for M times of channel characteristic information reporting can be simplified.

In another optional implementation, the time-frequency resource locations for the M times of channel characteristic information reporting can be configured in M CSI report configuration information (CSI report config), that is, M CSI report configs are configured, and each CSI report config can be used to configure the time-frequency resource location for reporting channel characteristic information.

In this way, the time-frequency resource location for each channel characteristic information report can be more flexibly configured.

As an optional implementation manner, the lengths of the second channel characteristic information reported M times are sequentially increased from the minimum length to the first length;

or,

The second channel characteristic information reported by the M times of channel characteristic information respectively includes non-overlapping parts of the first channel characteristic information, and the sum of the lengths of the second channel characteristic information reported by the M times of channel characteristic information is equal to the first length.

In an optional implementation manner, the lengths of the second channel characteristic information reported in the M times of channel characteristic information increase sequentially from the minimum length to the first length. At this time, the terminal sends the second channel characteristic information intercepted from the first channel characteristic information to the network side device respectively in M times of channel characteristic information reporting, including:

In the M times of reporting channel characteristic information, the terminal sends the second channel characteristic information to the network side device respectively according to the order of the length of the second channel characteristic information from short to long.

On the network side, the network side device can use the second channel characteristic information reported in order from short to long to gradually improve the accuracy of the restored channel information.

In another optional implementation, the second channel characteristic information reported for the M times of channel characteristic information respectively includes non-overlapping portions of the first channel characteristic information, and the M times of channel characteristic information reported are The sum of the lengths of the second channel characteristic information is equal to the first length. At this time, the terminal sends the second channel characteristic information intercepted from the first channel characteristic information to the network side device respectively in M times of channel characteristic information reporting, including:

In the M times of reporting channel characteristic information, the terminal sends the second channel characteristic information to the network side device according to the order in which the second channel characteristic information is arranged in the first channel characteristic information. interest.

In this way, the terminal can report non-overlapping channel characteristic information contents respectively during multiple channel characteristic information reporting processes. On the network side, the network side device can store the historical channel characteristic information that the terminal has reported, and report the second channel on the terminal. feature information, use the second channel feature information to update the reported historical channel feature information, and use the updated historical channel feature information as a whole to restore the channel information, which can reduce the second channel feature reported by the terminal. The amount of information can also be increased, and the amount of historical channel characteristic information used by network-side equipment for channel recovery can also be increased.

In this embodiment of the present application, the terminal uses the target AI network model to process the target channel information into the first channel characteristic information of the first length; the terminal sends the second channel characteristic information to the network side device, and the second channel characteristic information is the first channel characteristic information. Part of the channel characteristic information. In this way, in different channel environments, the terminal can adaptively use the same AI network model for encoding according to the length of the channel information, and only report part of the channel characteristic information of the corresponding length to the network side device, so that the network side uses the preconfigured The AI network model corresponding to the length is used to decode this part of the channel characteristic information, and can reduce the cost of transmitting the AI network model between the terminal and the network side device.

Referring to Figure 6, an embodiment of the present application provides a channel characteristic information recovery method. The execution subject may be a network side device. The terminal may be various types of network side devices 12 listed in Figure 1, or other than Network-side devices other than the network-side device types listed in the embodiment shown in FIG. 1 are not specifically limited here. As shown in Figure 6, the channel characteristic information recovery method may include the following steps:

Step 601: The network side device receives second channel characteristic information from the terminal, where the second channel characteristic information includes part of the first channel characteristic information, and the first channel characteristic information is the target AI network model adopted by the terminal. Channel characteristic information of the first length obtained by processing the target channel information.

In implementation, the above-mentioned first channel characteristic information, second channel characteristic information and target channel information respectively have the same characteristics as the first channel characteristic information, second channel characteristic information and target channel information in the method embodiment as shown in Figure 2. The meaning will not be elaborated here.

Step 602: The network side device uses the first AI network model to process the second channel characteristic information to obtain the target channel information.

In implementation, the network side device uses the first AI network model to process the second channel characteristic information to obtain the target channel information, which may be: the network side device uses a length corresponding to the second channel characteristic information. The first AI network model processes the second channel characteristic information to obtain the target channel information; or, the network side device uses at least two first AI network models corresponding to the second channel characteristic information to obtain the second channel characteristic information. The information is processed to obtain the target channel information.

As an optional implementation manner, the network side device receives the second channel characteristic information from the terminal, including:

The network side device receives second channel characteristic information of a second length intercepted from the first channel characteristic information from the terminal, and the second length is less than or equal to the first length.

The above-mentioned second length of second channel characteristic information has the same meaning as the second length of second channel characteristic information in the method embodiment shown in Figure 2, and also means that the terminal can determine the second length according to the instructions of the network side device. , or determine the second length according to the conditions agreed in the protocol, and report the second channel characteristic information of the second length to the network side device, which is not specifically limited here.

In a possible implementation, the network side device uses a first AI network model to process the second channel characteristic information to obtain the target channel information, which includes:

The network side device uses a first AI network model corresponding to the second channel characteristic information of the second length to process the second channel characteristic information of the second length to obtain the target channel information.

For example: As shown in Figure 7a, assume that one encoder corresponds to five decoders (decoder 1 to decoder 5 respectively), and each decoder has its own first AI network model. Each first AI The network models have corresponding second lengths: N0 to N4. In this way, each decoder can obtain the target channel information by decoding the corresponding second channel characteristic information of the second length.

In this implementation manner, the network side device uses a first AI network model corresponding to the second length each time to perform channel recovery.

In another possible implementation, the network side device uses a first AI network model to process the second channel characteristic information to obtain the target channel information, including:

In the case where the network side device stores historical channel characteristic information of the terminal, the The network side device updates the historical channel characteristic information according to the second channel characteristic information of the second length;

The network side device uses the first AI network model to process the updated historical channel characteristic information to obtain the target channel information.

In implementation, the above-mentioned network side device uses the first AI network model to process the updated historical channel characteristic information to obtain the target channel information, which may be: using an algorithm with the updated historical channel characteristic information. The first AI network model corresponding to the length processes the updated historical channel characteristic information to obtain the target channel information. For example: as shown in Figure 7a, assuming that the bit length of the updated historical channel characteristic information is the same as the decoded Corresponding to the decoder 5, the first AI network model in the decoder 5 is used to decode the updated historical channel characteristic information.

Of course, the above-mentioned network side device uses the first AI network model to process the updated historical channel characteristic information to obtain the target channel information, or it can also use the sum of the length and the updated historical channel characteristic information. /Or at least one first AI network model corresponding to the position in the first channel characteristic information processes the updated historical channel characteristic information to obtain the target channel information, for example: as shown in Figure 7b, assuming 1 encoder corresponds to 4 decoders (decoder 1 to decoder 4 respectively), and each decoder has its own first AI network model, and the second length corresponding to each first AI network model is the same (assuming the second length is N bits) but do not overlap each other. In this way, if the updated historical channel characteristic information includes second channel characteristic information corresponding to decoder 1 and decoder 2 respectively, the network side device can use the decoder The first AI network model in 1 decodes the corresponding second channel feature information, and uses the first AI network model in decoder 2 to decode the corresponding second channel feature information, and finally combines decoder 1 and decoding The decoding result of processor 2 is used to obtain the target channel information. That is, each decoder corresponds to the incremental part of the channel characteristic information, and the results of multiple decoders are combined to restore the channel information.

Optionally, before the network side device receives the second channel characteristic information of the second length intercepted from the first channel characteristic information from the terminal, the method further includes:

The network side device sends first indication information to the terminal, wherein the first indication information indicates the second length and/or a first encoding identifier, and the first encoding identifier is associated with the second length. .

Optionally, the first indication information is configured by high-level signaling; or,

The second channel characteristic information is carried in the channel state information CSI report, and the first indication information is indication information in the CSI report configuration, or the first indication information corresponds to the CSI resources used by the terminal.

Optionally, the channel characteristic information recovery method further includes:

The network side device receives second indication information from the terminal, and the second indication information indicates the second length.

Optionally, the second indication information is carried in a fixed-length CSI part in the CSI report, and the second channel characteristic information of the second length is carried in a variable-length CSI part in the CSI report; or,

The minimum length part of the second channel characteristic information of the second length and the second indication information are carried in the fixed length CSI part of the CSI report, and the second channel characteristic information of the second length except for the The variable length part other than the minimum length part is carried in the variable length CSI part in the CSI report; or,

The second indication information and the second channel characteristic information of the second length are both carried in the variable-length CSI part of the CSI report.

Optionally, the minimum length is less than or equal to the second length.

Optionally, the network side device receives second channel characteristic information from the terminal, including:

The network side device receives the second channel characteristic information respectively in the M times of channel characteristic information reporting by the terminal, where M is an integer greater than 1, and the second channel characteristic information reported by the M times of channel characteristic information is The lengths are different from each other, or the contents of the second channel characteristic information reported by the M times of channel characteristic information are different from each other.

Optionally, the network side device uses the first AI network model to process the second channel characteristic information to obtain the target channel information, including:

The network side device respectively uses M first AI network models to process the second channel characteristic information of corresponding lengths to obtain the target channel information. The corresponding lengths of the M first AI network models include the corresponding lengths. The length of the second channel characteristic information reported by the M times of channel characteristic information; or,

The network side device uses a first AI network model to process the second channel characteristic information reported by the M times of channel characteristic information to obtain the target channel information.

In an optional implementation, the above-mentioned network side device respectively uses M first AI network models to process the second channel characteristic information of corresponding lengths to obtain the target channel information, which is the same as the implementation shown in Figure 7b The examples are similar and have the same beneficial effects, so they will not be described again here.

In another optional implementation, the above network side device uses a first AI network model to process the second channel characteristic information reported by the M times of channel characteristic information to obtain the target channel information, as shown in Figure The embodiment shown in 7a is similar and has the same beneficial effects, and will not be described again here.

or,

Optionally, the lengths of the second channel characteristic information reported in the M times of channel characteristic information increase sequentially from the minimum length to the first length;

or,

The second channel characteristic information reported by the M times of channel characteristic information respectively includes non-overlapping parts of the channel characteristic information, and the sum of the lengths of the second channel characteristic information reported by the M times of channel characteristic information is equal to the First length.

Optionally, the network side device receives the second channel characteristic information reported from the terminal M times of channel characteristic information, including:

In the M times of channel feature information reporting by the terminal, the network side device receives the second channel feature information from the terminal in a preset order, and the preset order includes:

The length of the second channel characteristic information is arranged in order from short to long;

The order in which the second channel characteristic information is arranged in the first channel characteristic information.

In the embodiment of the present application, the network side device can use the first AI network model corresponding to the length of part of the first channel characteristic information reported by the terminal (that is, the second channel characteristic information) to perform channel recovery on the second channel characteristic information. , which can reduce the cost of transmitting AI network models between terminals and network-side devices.

In order to facilitate the explanation of the channel characteristic information reporting method and channel characteristic information recovery method provided by the embodiments of the present application, the embodiment of the present application uses the following interaction process of channel characteristic information as an example to illustrate the channel characteristic information reporting method and channel characteristic information provided by the embodiments of the present application. Feature information recovery method. In this embodiment, the interaction process of channel feature information includes the following steps:

Step 1. The terminal detects CSI-RS or TRS at the time-frequency domain location specified by the network, and performs channel estimation to obtain target channel information;

Step 2: The terminal encodes the target channel information into the first channel characteristic information through the target AI network model (i.e., AI encoding network model);

Step 3: The terminal selects part of the first channel characteristic information as the second channel characteristic information to be reported;

Step 4: The terminal combines the second channel characteristic information to be reported and other control information into uplink control information (UCI), or uses the second channel characteristic information to be reported as UCI;

Step 5. The terminal divides the UCI according to the length of the UCI and adds cyclic redundancy check (CRC) bits;

Step 6: The terminal performs channel coding on the UCI with CRC bits added;

Step 7. The terminal performs rate matching on UCI;

Step 8: The terminal performs code block association on UCI;

Step 9: The terminal maps the UCI to the Physical Uplink Control Channel (PUCCH) or Physical Uplink Shared Channel (PUSCH) for reporting.

It should be noted that in the above-mentioned interaction process of channel characteristic information, the order of some steps can be adjusted or omitted, and there is no specific limitation here.

For the channel characteristic information reporting method provided by the embodiments of this application, the execution subject may be the channel characteristic information Information reporting device. In the embodiment of the present application, the method for reporting channel characteristic information performed by the channel characteristic information reporting device is used as an example to illustrate the channel characteristic information reporting device provided by the embodiment of the present application.

Please refer to Figure 8. A device for reporting channel characteristic information provided by an embodiment of the present application can be a device in a terminal. As shown in Figure 8, the device 800 for reporting channel characteristic information can include the following modules:

The first processing module 801 is configured to use the target AI network model to process the target channel information into first channel characteristic information of a first length;

The first sending module 802 is configured to send second channel characteristic information to the network side device, where the second channel characteristic information is part of the first channel characteristic information.

Optional, the first sending module 802 is specifically used for:

Send second channel characteristic information of a second length intercepted from the first channel characteristic information to the network side device, where the second length is less than or equal to the first length.

Optionally, the first length is the number of bits of the first channel characteristic information, or the first length is the number of coefficients included in the first channel characteristic information; and/or,

The second length is the number of bits of the second channel characteristic information, or the second length is the number of coefficients included in the second channel characteristic information.

Optionally, the channel characteristic information reporting device 800 also includes:

A first receiving module configured to receive first indication information from the network side device, wherein the first indication information indicates the second length and/or a first encoding identifier, and the first encoding identifier is identical to the first encoding identifier. Describe the second length association.

The second channel characteristic information is carried in the channel state information CSI report, and the first indication information is the indication information in the CSI report configuration, or the first indication information is used by the terminal. Corresponds to the CSI resources used.

A determining module, configured to determine the second length according to at least one of channel characteristics and channel conditions corresponding to the target channel information.

A third sending module is configured to send second indication information to the network side device, where the second indication information indicates the second length.

Optionally, the second indication information is carried in a fixed-length CSI part in the CSI report, and the second length of the second channel characteristic information is carried in a variable-length CSI part in the CSI report; or,

The minimum length part of the second channel characteristic information of the second length and the fixed length CSI part of the second indication information are carried in the CSI report, and the second length of the second channel characteristic information except The variable-length part other than the minimum-length part is carried in the variable-length CSI part in the CSI report; or,

Optionally, the minimum length is less than or equal to the second length.

Optionally, the determination module is specifically used to perform any of the following:

According to the first association relationship, it is determined that the length of the value association of the target channel parameter of the target channel corresponding to the target channel information is the second length, wherein the first association relationship includes each value of the target channel parameter. Or the relationship between each value range and length;

According to the second association relationship, it is determined that the length corresponding to the encoding identifier associated with the value of the target channel parameter of the target channel corresponding to the target channel information is the second length, wherein the second association relationship includes the target channel parameter The association between each value or each value range and the coding identifier.

Optionally, the target channel parameters of the target channel include at least one of the following:

The target channel is line-of-sight propagation or non-line-of-sight propagation;

The number of effective delay paths of the target channel;

The delay interval between the two target paths of the target channel;

The number of effective beams of the target channel, the effective beams include beams corresponding to the discrete Fourier transform DFT orthogonal basis with power greater than the first threshold.

Optionally, the effective delay path includes at least one of the following:

The corresponding delay path whose power or amplitude is greater than the first threshold;

The delay path corresponding to the maximum power or amplitude.

The fourth receiving module is configured to receive relevant information of K first AI network models from the network side device, wherein the K first AI network models correspond to the target AI network model, and the K first AI network models correspond to the target AI network models. The first AI network model is used to decode the channel characteristic information of the respective corresponding lengths;

The determination module includes:

The second processing unit is configured to intercept K second channel characteristic information from the first channel characteristic information, and convert the second channel characteristic information of corresponding lengths through the K first AI network models. Processed into first channel information;

An acquisition unit, configured to acquire the degree of matching between K pieces of the first channel information and the target channel information respectively;

Determining unit, configured to determine that the second length is equal to the first length for processing to obtain the target first channel information when it is determined that the matching degree between the target first channel information and the target channel information satisfies a preset condition. The length corresponding to the AI network model, wherein the K pieces of first channel information obtained by processing the K pieces of the first AI network models include the target first channel information.

The target first channel information is the one in which the channel quality indicator CQI of the K pieces of first channel information is the same as or the closest to the CQI of the target channel information;

The target first channel information is one of the K pieces of first channel information in which the modulation and coding scheme MCS is the same as or closest to the MCS of the target channel information.

Optional, the first sending module 802 is specifically used for:

In the M times of channel characteristic information reporting, the second channel characteristic information intercepted from the first channel characteristic information is sent to the network side device respectively, where M is an integer greater than 1, and the M times of channel characteristic information reporting are The lengths of the second channel characteristic information are different from each other, or the contents of the second channel characteristic information reported by the M times of channel characteristic information are different from each other.

or,

Optionally, the lengths of the second channel characteristic information reported for the M times of channel characteristic information increase sequentially from the minimum length to the first length;

or,

Optional, the first sending module 802 is specifically used for:

In the M times of reporting channel characteristic information, the second channel characteristic information is sent to the network side device respectively in a preset order, and the preset order includes:

A channel estimation module, configured to perform channel estimation on the channel state information-reference signal CSI-RS or tracking reference signal TRS to obtain the target channel information; or,

A preprocessing module is used to preprocess the channel information obtained by channel estimation to obtain the target channel information.

The channel characteristic information reporting device 800 in the embodiment of the present application may be an electronic device, such as an electronic device with an operating system, or may be a component in the electronic device, such as an integrated circuit or chip. The electronic device may be a terminal or other devices other than the terminal. Example, terminal It may include but is not limited to the types of terminals 11 listed above. Other devices may be servers, network attached storage (Network Attached Storage, NAS), etc., which are not specifically limited in the embodiments of this application.

The channel characteristic information reporting device 800 provided by the embodiment of the present application can implement each process implemented by the method embodiment shown in Figure 2 and achieve the same technical effect. To avoid duplication, the details will not be described here.

For the channel characteristic information recovery method provided by the embodiments of the present application, the execution subject may be a channel characteristic information recovery device. In the embodiments of the present application, the channel characteristic information restoration method performed by the channel characteristic information restoration apparatus is used as an example to illustrate the channel characteristic information restoration apparatus provided by the embodiments of the present application.

Referring to Figure 9, a channel characteristic information recovery device provided by an embodiment of the present application can be a device in a network side device. As shown in Figure 9, the channel characteristic information recovery device 900 can include the following modules:

The second receiving module 901 is configured to receive second channel characteristic information from the terminal, where the second channel characteristic information includes part of the first channel characteristic information, and the first channel characteristic information is the target AI adopted by the terminal. The first length of channel characteristic information obtained by processing the target channel information by the network model;

The second processing module 902 is configured to use the first AI network model to process the second channel characteristic information to obtain the target channel information.

Optionally, the second receiving module 901 is specifically used for:

Receive second channel characteristic information of a second length intercepted from the first channel characteristic information from the terminal, where the second length is less than or equal to the first length.

Optionally, the second processing module 902 is specifically used to:

The first AI network model corresponding to the second channel characteristic information of the second length is used to process the second channel characteristic information of the second length to obtain the target channel information.

Optional, the second processing module 902 includes:

An update unit configured to update the historical channel characteristic information according to the second channel characteristic information of the second length when the network side device stores the historical channel characteristic information of the terminal;

The first processing unit is configured to use a first AI network model to process the updated historical channel characteristic information to obtain the target channel information.

Optionally, the channel characteristic information recovery device 900 also includes:

The fourth sending module is configured to send first indication information to the terminal, wherein the first indication information indicates the second length and/or a first encoding identifier, and the first encoding identifier is the same as the second encoding identifier. Length correlation.

A third receiving module is configured to receive second indication information from the terminal, where the second indication information indicates the second length.

Optionally, the second indication information is carried in a fixed-length CSI part of the CSI report, and the second length of the second channel characteristic information is carried in a variable-length CSI part of the CSI report; or,

The second indication information and the second channel characteristic information of the second length are both carried in the variable-length CSI part in the CSI report.

Optionally, the minimum length is less than or equal to the second length.

Optional, the second receiving module 901 is specifically used for:

In the M times of channel feature information reporting by the terminal, the second channel feature information is received respectively, where M is an integer greater than 1, and the lengths of the second channel feature information reported by the M times of channel feature information are different from each other, Or the contents of the second channel characteristic information reported in the M times of channel characteristic information are different from each other.

Optional, the second processing module 902 is specifically used to perform any of the following:

M first AI network models are respectively used to process the second channel characteristic information of corresponding lengths to obtain the target channel information, and the corresponding lengths of the M first AI network models include the M channel characteristics. The length of the second channel characteristic information reported;

A first AI network model is used to process the second channel characteristic information reported M times to obtain the target channel information.

or,

Optional, the second receiving module 901 is specifically used for:

In the M times of channel feature information reporting by the terminal, the second channel feature information from the terminal is received respectively in a preset order, and the preset order includes:

The channel characteristic information recovery device 900 in the embodiment of the present application may be an electronic device, such as an electronic device with an operating system, or may be a component in an electronic device, such as an integrated circuit or chip. The electronic device may be a network-side device, or may be other devices besides the network-side device. For example, the terminal may include but is not limited to the types of network side devices 12 listed above. Other devices may be servers, network attached storage (Network Attached Storage, NAS), etc., which are not specifically limited in the embodiment of this application.

The channel characteristic information recovery device 900 provided by the embodiment of the present application can implement each process implemented by the method embodiment shown in Figure 6 and achieve the same technical effect. To avoid duplication, the details will not be described here.

Optionally, as shown in Figure 10, this embodiment of the present application also provides a communication device 1000, which includes a processor 1001 and a memory 1002. The memory 1002 stores programs or instructions that can be run on the processor 1001, such as , when the communication device 1000 is a terminal, when the program or instruction is executed by the processor 1001, each step of the above channel characteristic information reporting method embodiment is implemented, and the same technical effect can be achieved. When the communication device 1000 is a network-side device, when the program or instruction is executed by the processor 1001, each step of the above channel characteristic information recovery method embodiment is implemented, and the same technical effect can be achieved. To avoid duplication, the details are not repeated here.

An embodiment of the present application also provides a terminal, including a processor and a communication interface. The processor is used to use the target AI network model to process the target channel information into first channel characteristic information of a first length; the communication interface is used to provide The network side device sends second channel characteristic information, and the second channel characteristic information is part of the first channel characteristic information.

This terminal embodiment corresponds to the above-mentioned terminal-side method embodiment. Each implementation process and implementation manner of the above-mentioned method embodiment can be applied to this terminal embodiment, and can achieve the same technical effect.

Specifically, FIG. 11 is a schematic diagram of the hardware structure of a terminal that implements an embodiment of the present application.

The terminal 1100 includes but is not limited to: a radio frequency unit 1101, a network module 1102, an audio output unit 1103, an input unit 1104, a sensor 1105, a display unit 1106, a user input unit 1107, an interface unit 1108, a memory 1109, a processor 1110, etc. At least some parts.

Those skilled in the art can understand that the terminal 1100 may also include a power supply (such as a battery) that supplies power to various components. The power supply may be logically connected to the processor 1110 through a power management system. The power management system is used to manage functions such as charging, discharging, and power consumption management. The terminal structure shown in FIG. 11 does not constitute a limitation on the terminal. The terminal may include more or fewer components than shown in the figure, or some components may be combined or arranged differently, which will not be described again here.

It should be understood that in the embodiment of the present application, the input unit 1104 may include a graphics processing unit (Graphics Processing Unit, GPU) 11041 and a microphone 11042. The graphics processor 11041 is responsible for the image capture device (GPU) in the video capture mode or the image capture mode. Process the image data of still pictures or videos obtained by cameras (such as cameras). The display unit 1106 may include a display panel 11061, which may be configured in the form of a liquid crystal display, an organic light-emitting diode, or the like. The user input unit 1107 includes at least one of a touch panel 11071 and other input devices 11072 . Touch panel 11071, also called touch screen. The touch panel 11071 may include two parts: a touch detection device and a touch controller. Other input devices 11072 may include but are not limited to physical keyboards, function keys (such as volume control keys, switch keys, etc.), trackballs, mice, and joysticks, which will not be described again here.

In this embodiment of the present application, after receiving downlink data from the network side device, the radio frequency unit 1101 can transmit it to the processor 1110 for processing; in addition, the radio frequency unit 1101 can send uplink data to the network side device. Generally, the radio frequency unit 1101 includes, but is not limited to, an antenna, amplifier, transceiver, coupler, low noise amplifier, duplexer, etc.

Memory 1109 may be used to store software programs or instructions as well as various data. The memory 1109 may mainly include a first storage area for storing programs or instructions and a second storage area for storing data, wherein the first storage area may store an operating system, an application program or instructions required for at least one function (such as a sound playback function, Image playback function, etc.) etc. Additionally, memory 1109 may include volatile memory or nonvolatile memory, or memory 1109 may include both volatile and nonvolatile memory. Among them, the non-volatile memory can be read-only memory (Read-Only Memory, ROM), programmable read-only memory (Programmable ROM, PROM), erasable programmable read-only memory (Erasable PROM, EPROM), electrically removable memory. Erase programmable read-only memory (Electrically EPROM, EEPROM) or flash memory. Volatile memory can be random access memory (Random Access Memory, RAM), static random access memory (Static RAM, SRAM), dynamic random access memory (Dynamic RAM, DRAM), synchronous dynamic random access memory (Synchronous DRAM, SDRAM), double data rate synchronous dynamic random access memory (Double Data Rate SDRAM, DDRSDRAM), enhanced synchronous dynamic random access memory (Enhanced SDRAM, ESDRAM), synchronous link dynamic random access memory (Synch link DRAM, SLDRAM) and direct memory bus random access memory (Direct Rambus RAM, DRRAM). Memory 1109 in embodiments of the present application includes, but is not limited to, these and any other suitable types of memory.

The processor 1110 may include one or more processing units; optionally, the processor 1110 integrates an application processor and a modem processor, where the application processor mainly handles operations related to the operating system, user interface, application programs, etc., Modem processors mainly process wireless communication signals, such as baseband processors. It can be understood that the above modem processor may not be integrated into the processor 1110.

The processor 1110 is configured to use the target AI network model to process the target channel information into first channel characteristic information of a first length;

The radio frequency unit 1101 is configured to send second channel characteristic information to the network side device, where the second channel characteristic information is part of the first channel characteristic information.

Optionally, the sending of the second channel characteristic information to the network side device performed by the radio frequency unit 1101 includes:

Optionally, before performing the sending of the second channel characteristic information of the second length intercepted from the first channel characteristic information to the network side device, the radio frequency unit 1101 is also configured to receive a third channel characteristic information from the network side device. an indication information, wherein the first indication information indicates the second length and/or A first encoding identifier, the first encoding identifier is associated with the second length.

Optionally, before the radio frequency unit 1101 performs the sending of the second channel characteristic information of the second length intercepted from the first channel characteristic information to the network side device, the processor 1110 is further configured to: At least one of channel characteristics and channel conditions corresponding to the information determines the second length.

Optionally, the radio frequency unit 1101 is also configured to send second indication information to the network side device, where the second indication information indicates the second length.

Optionally, the minimum length is less than or equal to the second length.

Optionally, the step performed by the processor 1110 to determine the second length according to the channel characteristics corresponding to the target channel information includes:

According to the first association relationship, it is determined that the length of the value association of the target channel parameter of the target channel corresponding to the target channel information is the second length, wherein the first association relationship includes each value of the target channel parameter. Or the relationship between each value range and length; or,

According to the second association relationship, it is determined that the length corresponding to the encoding identifier associated with the value of the target channel parameter of the target channel corresponding to the target channel information is the second length, wherein the second association relationship includes the target channel parameter The relationship between each value or each value range and the encoding identifier relationship.

The number of effective delay paths of the target channel;

The delay interval between the two target paths of the target channel;

Optionally, the effective delay path includes at least one of the following:

The delay path corresponding to the maximum power or amplitude.

Optionally, the radio frequency unit 1101 is also configured to receive relevant information of K first AI network models from the network side device, where the K first AI network models correspond to the target AI network model, The K first AI network models are respectively used to decode channel characteristic information of corresponding lengths;

Determining the second length according to channel conditions performed by the processor 1110 includes:

The processor 1110 intercepts K pieces of second channel characteristic information from the first channel characteristic information, and processes the corresponding lengths of the second channel characteristic information into first K pieces of first AI network models. channel information;

The processor 1110 obtains the matching degree of each of the K first channel information and the target channel information;

When the processor 1110 determines that the matching degree between the target first channel information and the target channel information satisfies the preset condition, the processor 1110 determines that the second length is equal to the first AI network used to process the target first channel information. The length corresponding to the model, wherein the K pieces of first channel information obtained by processing the K pieces of the first AI network models include the target first channel information.

The channel capacity of the target first channel information is greater than or equal to the channel capacity of the target channel information. The first preset value times the channel capacity, the first preset value is greater than 0 and less than or equal to 1;

In the M times of channel feature information reporting by the terminal, the second channel feature information intercepted from the first channel feature information is sent to the network side device respectively, where M is an integer greater than 1, and the M times channel The lengths of the second channel characteristic information reported by the characteristic information are different from each other, or the contents of the second channel characteristic information reported by the M times of channel characteristic information are different from each other.

or,

Optionally, in the M times of reporting channel characteristic information performed by the radio frequency unit 1101, the second channel characteristic information intercepted from the first channel characteristic information is sent to the network side device respectively, including:

Optionally, before the processor 1110 performs the process of using the target AI network model to process the target channel information into the first channel characteristic information of the first length:

The radio frequency unit 1101 is also used to perform channel estimation on the channel state information-reference signal CSI-RS or tracking reference signal TRS to obtain the target channel information; or,

The processor 1110 is also configured to preprocess the channel information obtained by channel estimation to obtain the target channel information.

The terminal 1100 provided by the embodiment of the present application can perform each process performed by each module in the channel characteristic information reporting device as shown in Figure 8, and can achieve the same beneficial effects. To avoid duplication, details will not be described here.

An embodiment of the present application also provides a network side device, including a processor and a communication interface. The communication interface is used to receive second channel characteristic information from a terminal, where the second channel characteristic information includes part of the first channel characteristic information. , the first channel characteristic information is the channel characteristic information of the first length obtained by the terminal using the target AI network model to process the target channel information; the processor is configured to use the first AI network model to process the second channel The characteristic information is processed to obtain the target channel information.

This network-side device embodiment corresponds to the above-mentioned network-side device method embodiment. Each implementation process and implementation manner of the above-mentioned method embodiment can be applied to this network-side device embodiment, and can achieve the same technical effect.

Specifically, the embodiment of the present application also provides a network side device. As shown in Figure 12, the network side device 1200 includes: an antenna 1201, a radio frequency device 1202, a baseband device 1203, a processor 1204 and a memory 1205. Antenna 1201 is connected to radio frequency device 1202. In the uplink direction, the radio frequency device 1202 receives information through the antenna 1201 and sends the received information to the baseband device 1203 for processing. In the downlink direction, the baseband device 1203 processes the information to be sent and sends it to the radio frequency device 1202. The radio frequency device 1202 processes the received information and then sends it out through the antenna 1201.

The method performed by the network side device in the above embodiment can be implemented in the baseband device 1203, which includes a baseband processor.

The baseband device 1203 may include, for example, at least one baseband board on which multiple chips are disposed, as shown in FIG. program to execute the network shown in the above method embodiment. network device operation.

The network side device may also include a network interface 1206, which is, for example, a common public radio interface (CPRI).

Specifically, the network side device 1200 in this embodiment of the present invention also includes: instructions or programs stored in the memory 1205 and executable on the processor 1204. The processor 1204 calls the instructions or programs in the memory 1205 to execute the various operations shown in Figure 9. The method of module execution and achieving the same technical effect will not be described in detail here to avoid duplication.

Embodiments of the present application also provide a readable storage medium. Programs or instructions are stored on the readable storage medium. When the program or instructions are executed by a processor, each process of the method embodiment shown in Figure 2 or Figure 6 is implemented. , and can achieve the same technical effect, so to avoid repetition, they will not be described again here.

Wherein, the processor is the processor in the terminal described in the above embodiment. The readable storage medium includes computer readable storage media, such as computer read-only memory ROM, random access memory RAM, magnetic disk or optical disk, etc.

An embodiment of the present application further provides a chip. The chip includes a processor and a communication interface. The communication interface is coupled to the processor. The processor is used to run programs or instructions. The implementation is as shown in Figure 2 or Figure 6. Each process of the method embodiment is shown, and the same technical effect can be achieved. To avoid repetition, the details will not be described here.

It should be understood that the chips mentioned in the embodiments of this application may also be called system-on-chip, system-on-a-chip, system-on-chip or system-on-chip, etc.

The embodiment of the present application further provides a computer program/program product, the computer program/program product is stored in a storage medium, and the computer program/program product is executed by at least one processor to implement Figure 2 or Figure 6 Each process of the method embodiment shown can achieve the same technical effect. To avoid repetition, it will not be described again here.

Embodiments of the present application also provide a communication system, including: a terminal and a network side device. The terminal can be used to perform the steps of the channel characteristic information reporting method as described above. The network side device can be used to perform the above steps. Steps of the channel characteristic information recovery method.

It should be noted that, in this document, the terms "comprising", "comprises" or any other variations thereof are intended to cover a non-exclusive inclusion, such that a process, method, article or device that includes a series of elements not only includes those elements, and include other elements not explicitly listed, or Includes elements inherent to such process, method, article or device. Without further limitation, an element defined by the statement "comprises a..." does not exclude the presence of additional identical elements in a process, method, article or apparatus that includes that element. In addition, it should be pointed out that the scope of the methods and devices in the embodiments of the present application is not limited to performing functions in the order shown or discussed, but may also include performing functions in a substantially simultaneous manner or in reverse order according to the functions involved. Functions may be performed, for example, the methods described may be performed in an order different from that described, and various steps may be added, omitted, or combined. Additionally, features described with reference to certain examples may be combined in other examples.

Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus the necessary general hardware platform. Of course, it can also be implemented by hardware, but in many cases the former is better. implementation. Based on this understanding, the technical solution of the present application can be embodied in the form of a computer software product that is essentially or contributes to the existing technology. The computer software product is stored in a storage medium (such as ROM/RAM, disk , CD), including several instructions to cause a terminal (which can be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in various embodiments of this application.

The embodiments of the present application have been described above in conjunction with the accompanying drawings. However, the present application is not limited to the above-mentioned specific implementations. The above-mentioned specific implementations are only illustrative and not restrictive. Those of ordinary skill in the art will Inspired by this application, many forms can be made without departing from the purpose of this application and the scope protected by the claims, all of which fall within the protection of this application.

Claims

A method for reporting channel characteristic information, including:

The terminal uses the target AI network model to process the target channel information into the first channel characteristic information of the first length;

The terminal sends second channel characteristic information to the network side device, where the second channel characteristic information is part of the first channel characteristic information.
The method according to claim 1, wherein the terminal sends the second CSI information to the network side device, including:

The terminal sends a second length of second channel characteristic information intercepted from the first channel characteristic information to the network side device, and the second length is less than or equal to the first length.
The method according to claim 2, wherein the first length is the number of bits of the first channel characteristic information, or the first length is the number of coefficients included in the first channel characteristic information. ;and / or,

The second length is the number of bits of the second channel characteristic information, or the second length is the number of coefficients included in the second channel characteristic information.
The method of claim 2, wherein the second length of second channel characteristic information includes at least one of the following:

For the first N bits or coefficients in the first channel characteristic information, N is equal to the number of bits corresponding to the second length or the number of coefficients corresponding to the second length;

N bits or coefficients in the first channel characteristic information whose importance level is greater than the preset level;

N bits or coefficients in the first channel characteristic information other than the reported channel characteristic information.
The method according to claim 2 or 4, wherein before the terminal sends the second channel characteristic information of the second length intercepted from the first channel characteristic information to the network side device, the method further includes:

The terminal receives first indication information from the network side device, wherein the first indication information indicates the second length and/or a first encoding identifier, and the first encoding identifier and the second length association.
The method according to claim 5, wherein the first indication information is configured by high-layer signaling; or,

The second channel characteristic information is carried in the channel state information CSI report, and the first indication information is indication information in the CSI report configuration, or the first indication information corresponds to the CSI resources used by the terminal.
The method according to claim 2 or 4, wherein before the terminal sends the second channel characteristic information of the second length intercepted from the first channel characteristic information to the network side device, the method further includes:

The terminal determines the second length according to at least one of channel characteristics and channel conditions corresponding to the target channel information.
The method of claim 7, further comprising:

The terminal sends second indication information to the network side device, and the second indication information indicates the second length.
The method of claim 8, wherein the second indication information is carried in a fixed-length CSI part of the CSI report, and the second length of the second channel characteristic information is carried in a variable part of the CSI report. the CSI portion of the length; or,

The minimum length part of the second channel characteristic information of the second length and the second indication information are carried in the fixed length CSI part of the CSI report, and the second length of the second channel characteristic information is carried in the fixed length CSI part of the CSI report. A variable length part other than the minimum length part is carried in the variable length CSI part in the CSI report; or,

The second indication information and the second channel characteristic information of the second length are both carried in the variable-length CSI part in the CSI report.
The method of claim 9, wherein the minimum length is less than or equal to the second length.
The method according to claim 7, wherein the terminal determines the second length according to the channel characteristics corresponding to the target channel information, including:

The terminal determines that the length of the value association of the target channel parameter of the target channel corresponding to the target channel information is the second length according to the first association relationship, wherein the first association relationship includes the value of the target channel parameter. The relationship between each value or each value range and length; or By,

The terminal determines that the length corresponding to the encoding identifier associated with the value of the target channel parameter of the target channel corresponding to the target channel information is the second length according to the second association relationship, wherein the second association relationship includes the The correlation between each value or each value range of the target channel parameter and the coding identifier.
The method according to claim 11, wherein the target channel parameters of the target channel include at least one of the following:

The target channel is line-of-sight propagation or non-line-of-sight propagation;

The number of effective delay paths of the target channel;

The delay interval between the two target paths of the target channel;

The number of effective beams of the target channel, the effective beams include beams corresponding to the discrete Fourier transform DFT orthogonal basis with power greater than the first threshold.
The method according to claim 12, wherein the effective delay path includes at least one of the following:

The corresponding delay path whose power or amplitude is greater than the first threshold;

The delay path corresponding to the maximum power or amplitude.
The method of claim 7, further comprising:

The terminal receives relevant information of K first AI network models from the network side device, wherein the K first AI network models correspond to the target AI network model, and the K first AI network models The models are respectively used to decode the channel characteristic information of their corresponding lengths;

The terminal determines the second length according to channel conditions, including:

The terminal intercepts K pieces of second channel characteristic information from the first channel characteristic information, and processes the second channel characteristic information of corresponding lengths into first K pieces of first AI network models respectively. channel information;

The terminal obtains the degree of matching between the K pieces of the first channel information and the target channel information respectively;

When the terminal determines that the matching degree between the target first channel information and the target channel information satisfies a preset condition, the terminal determines that the second length is equal to the first AI network used to process the target first channel information. The corresponding length of the model, where K of the first AI network models process The obtained K first channel information includes the target first channel information.
The method according to claim 14, wherein the matching degree between the target first channel information and the target channel information satisfying a preset condition includes at least one of the following:

The correlation between the target first channel information and the target channel information is greater than or equal to a preset correlation;

The channel capacity of the target first channel information is greater than or equal to a first preset value times the channel capacity of the target channel information, and the first preset value is greater than 0 and less than or equal to 1;

The target first channel information is the one in which the channel quality indicator CQI of the K pieces of first channel information is the same as or the closest to the CQI of the target channel information;

The target first channel information is one of the K pieces of first channel information in which the modulation and coding scheme MCS is the same as or closest to the MCS of the target channel information.
The method according to claim 1, wherein the terminal sends the second channel characteristic information to the network side device, including:

In the M times of channel feature information reporting, the terminal sends the second channel feature information intercepted from the first channel feature information to the network side device respectively, where M is an integer greater than 1, and the M times channel feature information The lengths of the second channel characteristic information reported by the information are different from each other, or the contents of the second channel characteristic information reported by the M times of channel characteristic information are different from each other.
The method according to claim 16, wherein, in the case where the second channel characteristic is carried in the CSI report, the time-frequency resource location of the M times of channel characteristic information reporting is configured by a piece of CSI report configuration information;

or,

The time-frequency resource locations for the M channel characteristic information reports are configured by M pieces of CSI report configuration information.
The method according to claim 16, wherein the length of the second channel characteristic information reported M times increases sequentially from the minimum length to the first length;

or,

The second channel characteristic information reported by the M times of channel characteristic information respectively includes non-overlapping parts of the first channel characteristic information, and the sum of the lengths of the second channel characteristic information reported by the M times of channel characteristic information is equal to the first length.
The method according to any one of claims 16 to 18, wherein the terminal sends the second channel characteristics intercepted from the first channel characteristic information to the network side device respectively in M times of channel characteristic information reporting. information, including:

In the M times of channel feature information reporting, the terminal sends the second channel feature information to the network side device in a preset sequence, and the preset sequence includes:

The length of the second channel characteristic information is arranged in order from short to long;

The order in which the second channel characteristic information is arranged in the first channel characteristic information.
The method according to claim 1, wherein before the terminal uses the target AI network model to process the target channel information into the first channel characteristic information of the first length, the method further includes:

The terminal performs channel estimation on the channel state information-reference signal CSI-RS or tracking reference signal TRS to obtain the target channel information; or,

The terminal preprocesses the channel information obtained by channel estimation to obtain the target channel information.
A device for reporting channel characteristic information, applied to terminals, the device includes:

The first processing module is used to process the target channel information into first channel characteristic information of the first length using the target AI network model;

The first sending module is configured to send second channel characteristic information to the network side device, where the second channel characteristic information is part of the first channel characteristic information.
A method for recovering channel characteristic information, including:

The network side device receives the second channel characteristic information from the terminal, wherein the second channel characteristic information includes part of the first channel characteristic information, and the first channel characteristic information is the target channel adopted by the terminal using the target AI network model. The first length of channel characteristic information obtained by processing the information;

The network side device uses the first AI network model to process the second channel characteristic information to obtain the target channel information.
The method according to claim 22, wherein the network side device receives the second channel characteristic information from the terminal, including:

The network side device receives from the terminal a second channel characteristic information intercepted from the first channel characteristic information. length of the second channel characteristic information, where the second length is less than or equal to the first length.
The method according to claim 23, wherein the network side device uses a first AI network model to process the second channel characteristic information to obtain the target channel information, including:

The network side device uses a first AI network model corresponding to the second channel characteristic information of the second length to process the second channel characteristic information of the second length to obtain the target channel information.
The method according to claim 23, wherein the network side device uses a first AI network model to process the second channel characteristic information to obtain the target channel information, including:

In the case where the network side device stores the historical channel characteristic information of the terminal, the network side device updates the historical channel characteristic information according to the second channel characteristic information of the second length;

The network side device uses the first AI network model to process the updated historical channel characteristic information to obtain the target channel information.
The method according to any one of claims 23 to 25, wherein before the network side device receives the second channel characteristic information of the second length intercepted from the first channel characteristic information from the terminal, the The above methods also include:

The network side device sends first indication information to the terminal, wherein the first indication information indicates the second length and/or a first encoding identifier, and the first encoding identifier is associated with the second length. .
The method according to any one of claims 23 to 25, wherein the method further comprises:

The network side device receives second indication information from the terminal, and the second indication information indicates the second length.
The method according to claim 22, wherein the network side device receives the second channel characteristic information from the terminal, including:

The network side device receives the second channel characteristic information respectively in the M times of channel characteristic information reporting by the terminal, where M is an integer greater than 1, and the second channel characteristic information reported by the M times of channel characteristic information is The lengths are different from each other, or the contents of the second channel characteristic information reported by the M times of channel characteristic information are different from each other.
The method of claim 28, wherein the second channel characteristic is carried in the CSI In the case of reporting, the time-frequency resource location for the M channel characteristic information reports is configured by a piece of CSI report configuration information;

or,

The time-frequency resource locations for the M channel characteristic information reports are configured by M pieces of CSI report configuration information.
A channel characteristic information recovery device, applied to network side equipment, the device includes:

The second receiving module is configured to receive second channel characteristic information from the terminal, wherein the second channel characteristic information includes part of the first channel characteristic information, and the first channel characteristic information is the target AI network adopted by the terminal. The first length of channel characteristic information obtained by processing the target channel information by the model;

The second processing module is configured to use the first AI network model to process the second channel characteristic information to obtain the target channel information.
A terminal, including a processor and a memory, the memory stores programs or instructions that can be run on the processor, and when the programs or instructions are executed by the processor, any one of claims 1 to 20 is implemented. The steps of the method for reporting channel state information and channel characteristic information.
A network-side device includes a processor and a memory. The memory stores programs or instructions that can be run on the processor. When the program or instructions are executed by the processor, any one of claims 22 to 29 is implemented. The steps of the channel state information channel characteristic information recovery method described in one item.
A readable storage medium storing programs or instructions on the readable storage medium. When the programs or instructions are executed by a processor, the reporting of channel status information and channel characteristic information as described in any one of claims 1 to 20 is achieved. The steps of the method, or the steps of realizing the channel characteristic information recovery method according to any one of claims 22 to 29.