CN113556299A

CN113556299A - Self-adaptive blind detection method, device, equipment and medium

Info

Publication number: CN113556299A
Application number: CN202110616328.6A
Authority: CN
Inventors: 朱洪飞; 汪奕汝; 赵玉萍; 李斗
Original assignee: Beijing Hannuo Semiconductor Technology Co ltd; Peking University
Current assignee: Beijing Hannuo Semiconductor Technology Co ltd; Peking University
Priority date: 2021-06-02
Filing date: 2021-06-02
Publication date: 2021-10-26

Abstract

The present disclosure relates to an adaptive blind detection method, apparatus, medium, and device, wherein the method comprises: initializing a current list size L of a successive elimination list decoding algorithm_nowInitial value of (2) and maximum list size L_max(ii) a And decoding all the physical downlink control channels by using the continuous elimination list decoding algorithm and performing cyclic redundancy check, wherein if the physical downlink control channel candidate passes the cyclic redundancy check, the user equipment succeeds in blind detection, and the process is ended. Simulation results show that the adaptive blind test provided by the disclosure can greatly reduce an average L value required by a blind test process on the premise of realizing the same Missed Detection Rate (MDR) as that of a single-stage blind test and a double-stage blind test, thereby remarkably reducing the time complexity of the blind test.

Description

Self-adaptive blind detection method, device, equipment and medium

Technical Field

The present disclosure relates to the field of internet technologies, and more particularly, to a method, an apparatus, a device, and a medium for adaptive blind detection.

Background

In the 5G (5th Generation mobile networks, fifth Generation mobile networks) NR (New Radio, New air interface) standard, a PDCCH (Physical downlink Control Channel) carries scheduling and resource allocation information of a specific UE (User Equipment), such as downlink resource allocation, uplink grant, random access response, uplink power Control command, and common scheduling assignment of signaling messages (such as system messages and paging messages).

On the PDCCH, a basic element for carrying DCI (Downlink Control Information) is a CCE (Control channel element). The UE generally does not know the number of CCEs occupied by the current PDCCH, what DCI format information is transmitted, and where the information it needs is. But the UE knows what information it is currently expecting, e.g. the information that the UE expects in Idle state is paging SI; RACH Response is expected after Random Access is initiated; expecting a UL Grant when uplink data waits to be transmitted; DCI for format 1A or format 2A, etc. is expected in TM3 mode. For different pieces of desired information, the UE uses corresponding RNTI (Radio Network Temporary Identity) and CCE information to perform CRC (Cyclic Redundancy Check) Check, and if the CRC Check is successful, the UE knows that the information is required by itself, and may further know corresponding DCI format and modulation mode, thereby resolving the DCI content, which is a so-called blind Check process. In 5G, the DCI information is encoded by using a Polar code, and in order to find the DCI information belonging to the UE, the UE needs to perform multiple blind detections on all possible DCI information in a Search Space (Search Space) specified by a PDCCH (physical Downlink control channel) and the decoding process of code words of multiple Polar codes is involved, so the decoding speed of the Polar codes becomes a problem which needs to be concerned by the design of a 5G system.

Disclosure of Invention

The method aims to solve the technical problem that the classification model in the prior art cannot meet the actual requirements of users on adaptive blind detection.

In order to achieve the technical purpose, the present disclosure provides an adaptive blind detection method, including:

initializing successive erasure columnsCurrent list size L of a list decoding algorithm_nowInitial value of (2) and maximum list size L_max；

And decoding all the physical downlink control channels by using the continuous elimination list decoding algorithm and performing cyclic redundancy check, wherein if the physical downlink control channel candidate passes the cyclic redundancy check, the user equipment succeeds in blind detection, and the process is ended.

Further, after decoding all the physical downlink control channels by using the continuous cancellation list decoding algorithm and performing cyclic redundancy check, the method further includes:

if the decoding algorithm of the continuous elimination list completes the cyclic redundancy check on all the physical downlink control channel candidates and none of the physical downlink control channel candidates passes the cyclic redundancy check, the size L of the current list is determined_nowIs increased and the current list size L is performed_nowWhether or not it is less than or equal to the maximum list size L_maxIf yes, continuing to execute the step of decoding all physical downlink control channels by using the continuous elimination list decoding algorithm and performing cyclic redundancy check, otherwise, ending the blind test if the current user equipment does not find the wireless network temporary identifier.

Further, the current list size L_nowIs increased by the current list size L_nowThe numerical value of (A) is doubled.

Further, the initializing a current list size L of a successive elimination list coding algorithm_nowThe initial values of (a) are specifically:

initializing a current list size L of a successive elimination list decoding algorithm_nowIs an initial value of 1.

To achieve the above technical object, the present disclosure can also provide an adaptive blind detection apparatus, including:

an initialization module for initializing a current list size L of a successive elimination list decoding algorithm_nowIs an initial value of 1 and a maximum list size L_max；

And the cyclic redundancy check module is used for decoding all the physical downlink control channels by using the continuous elimination list decoding algorithm and performing cyclic redundancy check, and if the physical downlink control channel candidate passes the cyclic redundancy check, the user equipment succeeds in blind check.

Further, still include:

a judging module, configured to, if the consecutive elimination list decoding algorithm completes cyclic redundancy check on all the physical downlink control channel candidates and none of the physical downlink control channel candidates passes cyclic redundancy check, determine a size L of the current list_nowIs increased and the current list size L is performed_nowWhether or not it is less than or equal to the maximum list size L_maxIf yes, continuing to execute the step of decoding all physical downlink control channels by using the continuous elimination list decoding algorithm and performing cyclic redundancy check, otherwise, ending the blind test if the current user equipment does not find the wireless network temporary identifier.

To achieve the above technical object, the present disclosure can also provide a computer storage medium having a computer program stored thereon, the computer program being executed by a processor for implementing the steps of the adaptive blind detection method described above.

To achieve the above technical object, the present disclosure further provides an electronic device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the adaptive blind detection method when executing the computer program.

The beneficial effect of this disclosure does:

multiple averaging of SCL coding of different L valuesThe inter-complexity can be expressed as O (L)_avgNlogN), wherein L_avgIs the average L value. Compared with a two-stage blind detection scheme, the adaptive blind detection method can fully play the potential of the SCL decoding algorithm corresponding to a smaller L value, and further reduce the L required by the blind detection_avgThereby reducing the time complexity of averaging. And the higher the signal-to-noise ratio is, the higher the possibility that the CRC check can be successful by adopting the SCL decoding algorithm with smaller L in the adaptive blind test is, so that the time complexity gain is larger.

From the analysis of the performance, the performance of the adaptive algorithm is L ═ L_maxShould be nearly identical. Because if the adaptive algorithm is in L < L_maxIf the blind test is successful, the performance is the same as that of using L ═ L only_maxThe single-stage blind tests are almost the same (the false alarm rate can be ignored); if the adaptive algorithm is in L < L_maxIf the blind test fails, L is increased until L equals L_maxThe performance is equal to that of only L ═ L_maxIs naturally the same.

Drawings

Figure 1 shows a schematic diagram of radio network temporary identity RNTI scrambling codes;

FIG. 2 shows a flow chart of a method of embodiment 1 of the present disclosure;

FIG. 3 shows k₁＝16，k₂MDR performance comparison for 57 three algorithms;

FIG. 4 shows k₁＝16，k₂57 algorithm L_avgComparing;

FIG. 5 shows k₁＝40，k₂MDR performance comparison of 42 three algorithms;

FIG. 6 shows k₁＝40，k₂42 for three algorithms L_avgComparing;

fig. 7 shows a schematic structural diagram of embodiment 2 of the present disclosure;

fig. 8 shows a schematic structural diagram of embodiment 4 of the present disclosure.

Detailed Description

Hereinafter, embodiments of the present disclosure will be described with reference to the accompanying drawings. It should be understood that the description is illustrative only and is not intended to limit the scope of the present disclosure. Moreover, in the following description, descriptions of well-known structures and techniques are omitted so as to not unnecessarily obscure the concepts of the present disclosure.

Various structural schematics according to embodiments of the present disclosure are shown in the figures. The figures are not drawn to scale, wherein certain details are exaggerated and possibly omitted for clarity of presentation. The shapes of various regions, layers, and relative sizes and positional relationships therebetween shown in the drawings are merely exemplary, and deviations may occur in practice due to manufacturing tolerances or technical limitations, and a person skilled in the art may additionally design regions/layers having different shapes, sizes, relative positions, as actually required.

The search space in 5G is divided into two types: common Search Space (CSS) and UE Specific Search Space (USS). CSS is mainly used at access and cell handover, whereas USS is used after access. The type and classification of the 5G search space are shown in table 1.1.

TABLE 1.15G types and classifications of search spaces

In LTE (Long Term Evolution), there is only the concept of search space and not the concept of Control Resource SET (CORESET), and the NR system introduces the concept of CORESET. This is because, in the LTE system, the PDCCH occupies the entire Frequency band in the Frequency domain, occupies the first 1-3 OFDM (Orthogonal Frequency Division Multiplexing) symbols of each subframe in the time domain, and the start position is fixed to the #0 OFDM symbol. That is, the system only needs to inform the user of the number of OFDM symbols occupied by the PDCCH, and the UE can determine the search space of the PDCCH. In the NR system, since the bandwidth of the system (which may be 400MHz at maximum) is large, if the PDCCH still occupies the entire bandwidth, resources are wasted, and the blind detection complexity is also large. In addition, NR, in order to increase system flexibility, the starting position of PDCCH in the time domain may also be configurable. Therefore, in the 5G NR, the UE needs to completely acquire the time-frequency domain resource allocation information of the PDCCH to further demodulate the PDCCH.

In 5G, CORESET contains 1/2/3 OFDM symbols in the time domain and an integer multiple of the 6 REG bandwidth in the frequency domain. In 5G, the relationship between Search Space and CORESET is: the NR system packages information such as frequency bands occupied on a PDCCH frequency domain, OFDM symbol number occupied on a time domain and the like in CORESET; encapsulating information such as a PDCCH initial OFDM symbol number, a PDCCH monitoring period and associated CORESET and the like in a Search Space; the configuration of the PDCCH can only be determined after one core Space and one Search Space are bound together, and one core Space can be bound with a plurality of Search spaces, but one Search Space can be bound with only one core Space.

The length of the DCI is determined by DCI format. The DCI formats corresponding to the 5G different purposes are shown in the table. It can be seen that there are at most two DCI formats, i.e. at most two payload lengths, for a signal to be received by a UE in a certain state.

TABLE 1.25G DCI Format for different applications

In 5G, the DCI information adopts Polar coding, as shown in FIG. 1. The end of the k-bit payload (valid information bits) is added with m-bit CRC, where k ≦ 140 and m ≦ 24. The last 16 bits of the CRC check bits are then scrambled by the 16-bit RNTI of the UE, and we can then get K ═ K + m information bits. Then, the information bits become code words with length of N after being coded by Polar codes. In 5G, N takes on three values, 128, 256 and 512.

The basic flow of 5G blind detection is as follows:

1) determining the time domain resource scheduling condition of a PDCCH Candidate (Candidate) according to the current Search Space and the associated CORESET configuration, wherein the time domain starting symbol position is determined by the current Search Space configuration, and the time domain symbol number is determined by the CORESET associated with the Search Space;

2) determining CCE indexes (namely the initial positions of the CCEs and the number of the CCEs) of each PDCCH Candidate in the CORESET according to the current Search Space and the associated CORESET configuration, wherein the specific CCEs are determined through a Search Space function;

and performing Polar decoding and CRC (cyclic redundancy check) on each PDCCH Candidate, wherein when the CRC passes, the current PDCCH Candidate is successfully demodulated. Note that the number of blind decodes depends on the subcarrier spacing. For subcarrier spacing of 15, 30, 60, 120kHz, a maximum of 44, 36, 22, 20 decoding attempts (these also include different DCI payload lengths) per slot response is supported. The maximum number of decoding attempts defined by the NR standard provides a balance between terminal implementation complexity and scheduling flexibility.

In the currently commercially available 5G scheme, a single-stage blind detection scheme is adopted at the UE end. The specific implementation process is as follows: when the UE performs blind detection on the PDCCH, it sequentially performs SCL (consecutive Cancellation List) decoding on all received pdcchcandidates, and the commonly used L value is 8. After SCL decoding of each PDCCHCbinary is finished to obtain a payload and CRC check bits, the UE descrambles the CRC check bits by using the RNTI of the UE and then performs CRC check on the payload. Once the UE finds that the CRC of one PDCCH Candidate passes, the UE considers that the PDCCH Candidate belongs to the UE, and the blind test is finished; if the UE does not find any PDCCHCindex can pass the CRC, the blind detection is also finished, and the base station is considered not to transmit the control information belonging to the base station.

If the base station sends the control information belonging to the UE, but the UE is not detected finally, the UE considers that the Detection is a Missed Detection, and the corresponding probability is called a Missed Detection Rate (MDR); if the base station does not send the control information belonging to the UE, but the UE is detected finally, it is considered as a false alarm, and the corresponding probability is called a False Alarm Rate (FAR).

Because the decoding time complexity of the SCL algorithm is O (LNlogN), the traditional single-stage blind testThe complexity of the algorithm is high. Therefore, a two-stage decoding scheme is proposed in the literature, i.e., a low-complexity SCL is used first (L ═ L)₁) The decoding algorithm performs primary screening on all PDCCHCbinary, and once PDCCHCbinary passing CRC check exists, the PDCCHCbinary is considered to belong to the decoding algorithm, and blind detection is finished. If none of the PDCCHCAndidates can pass the CRC check after the SC decoding of all PDCCHCAndidates is finished, all PDCCHCAndidates are taken to be performed with SCL with high complexity (L ═ L-₂) And (5) decoding.

The first stage of two-stage blind test usually adopts SC decoding, namely L ₁1. The SC decoding algorithm has a time complexity of O (NlogN) and is 1/L of the SCL decoding algorithm. In most cases, after the first SC decoding is primarily screened, the CRC check can be successful, and the second stage SCL decoding is needed in few cases. Compared with a single-stage blind detection scheme, the blind detection complexity of the two stages can be greatly reduced, and the higher the signal-to-noise ratio is, the higher the ratio of the blind detection success of the first stage is, so that the more the complexity is reduced.

The first embodiment is as follows:

as shown in fig. 2:

the present disclosure provides an adaptive blind detection method, comprising:

s101: initializing a current list size L of a successive elimination list decoding algorithm_nowInitial value of (2) and maximum list size L_max；

S102: and decoding all the physical downlink control channels by using the continuous elimination list decoding algorithm and performing cyclic redundancy check, wherein if the physical downlink control channel candidate passes the cyclic redundancy check, the user equipment succeeds in blind detection, and the process is ended.

if the decoding algorithm of the continuous elimination list completes the cyclic redundancy check on all the physical downlink control channel candidates, no physical downlink control channel existsIf the candidate passes the cyclic redundancy check, the current list size L is set_nowIs increased and the current list size L is performed_nowWhether or not it is less than or equal to the maximum list size L_maxIf yes, continuing to execute the step of decoding all physical downlink control channels by using the continuous elimination list decoding algorithm and performing cyclic redundancy check, otherwise, ending the blind test if the current user equipment does not find the wireless network temporary identifier.

The adaptive blind detection method of the present disclosure is explained in detail below with reference to simulation results:

the experimental platform is configured with two Polar code lengths: n is a radical of₁＝256，N₂512. The number of PDCCH candidates at each code length is 11, i.e. a total of 22 pdcchcodes are transmitted by the base station. For each PDCCHCindex, the base station randomly selects K₁And K₂One of the two information bit lengths performs information bit configuration. CRC bit length m is 24 corresponding to two payload lengths k₁＝K₁-m，k₂＝K₂-m. Among all PDCCHRandidates, only one is scrambled with the RNTI of the current UE, and the other PDCCHRandidates are scrambled with the RNTIs of the other UEs.

Currently, the UE needs to pair K for each PDCCH Candidate received₁And K₂Both information bit lengths perform decoding attempts, i.e. the number of blind detections required by the UE is 22 × 2-44. And (3) configuration of a receiving terminal SCL decoding algorithm: for single-stage blind test, L is 8; for two-stage blind inspection, the first stage L ₁1, second stage L ₂8; for adaptive blind detection, L _max8. We compare the MDR and L of the three algorithms_avgWith the variation of Signal-to-Noise Ratio (SNR).

k₁＝16，k₂＝57

We first simulate two cases where the difference in payload length is large, here we take k₁＝16，k₂The MDR performance of the three algorithms is compared as shown in fig. 3, 57. As can be seen from the figure, the MDR performance curves of the three algorithms completely coincide, and the scheme of the adaptive blind test proposed by the inventor achieves the same performance as that of the single-stage blind test and the two-stage blind test. Then we compared L of the three algorithms_avgAs shown in fig. 4. It can be seen that the single-stage blind test uses the fixed SCL8 decoding, so its L_avgAnd fixed to 8. The two-stage blind test increases a certain degree of self-adaptability on the basis of the single-stage blind test, so the L of the two-stage blind test is_avgThe reduction is very significant. The scheme of the adaptive blind detection provided by the patent has a low passing proportion when a small L value is used in a low signal-to-noise ratio (less than or equal to-2 dB), so that the decoding can be successfully carried out only by increasing L to a large value, and the L is caused_avgMore than two stages of blind detection; however, as the signal-to-noise ratio is increased (more than-2 dB), the adaptive blind test can be successfully carried out only by a smaller L value, thereby greatly reducing L_avgAnd the higher the signal-to-noise ratio is, the larger the time complexity gain brought by the adaptive blind detection is.

k₁＝40，k₂＝42

Then we simulate two cases where the payload length is not very different, here we take k₁＝40，k₂42. MDR comparison and L of three algorithms_avgIn comparison, as shown in fig. 5 and 6, respectively. It can be seen in fig. 5 that the MDR performance curves of the three algorithms still completely coincide under the present parameter configuration. However, unlike FIG. 4, L of the adaptive blind test shown in FIG. 6_avgThe performance is better than the two-stage blind detection scheme in the whole signal-to-noise ratio range. I.e. at k₁And k₂Under the condition of not being different, the time complexity gain brought by the algorithm is more obvious, and the time complexity gain is more obviousThe superiority of the scheme is highlighted.

Example two:

as shown in figure 7 of the drawings,

the present disclosure can also provide an adaptive blind detection apparatus, including:

an initialization module 201 for initializing the current list size L of the consecutive elimination list decoding algorithm_nowIs an initial value of 1 and a maximum list size L_max；

And a cyclic redundancy check module 202, configured to decode all the physical downlink control channels by using the continuous cancellation list decoding algorithm and perform cyclic redundancy check, and if there is a physical downlink control channel candidate that passes the cyclic redundancy check, the user equipment blind check is successful.

The initialization module 201 is connected to the cyclic redundancy check module 202.

Further, the apparatus further comprises:

Example three:

the present disclosure can also provide a computer storage medium having stored thereon a computer program for implementing the steps of the adaptive blind detection method described above when executed by a processor.

The computer storage medium of the present disclosure may be implemented with a semiconductor memory, a magnetic core memory, a magnetic drum memory, or a magnetic disk memory.

Semiconductor memories are mainly used as semiconductor memory elements of computers, and there are two types, Mos and bipolar memory elements. Mos devices have high integration, simple process, but slow speed. The bipolar element has the advantages of complex process, high power consumption, low integration level and high speed. NMos and CMos were introduced to make Mos memory dominate in semiconductor memory. NMos is fast, e.g. 45ns for 1K bit sram from intel. The CMos power consumption is low, and the access time of the 4K-bit CMos static memory is 300 ns. The semiconductor memories described above are all Random Access Memories (RAMs), i.e. read and write new contents randomly during operation. And a semiconductor Read Only Memory (ROM), which can be read out randomly but cannot be written in during operation, is used to store solidified programs and data. The ROM is classified into a non-rewritable fuse type ROM, PROM, and a rewritable EPROM.

The magnetic core memory has the characteristics of low cost and high reliability, and has more than 20 years of practical use experience. Magnetic core memories were widely used as main memories before the mid 70's. The storage capacity can reach more than 10 bits, and the access time is 300ns at the fastest speed. The typical international magnetic core memory has a capacity of 4 MS-8 MB and an access cycle of 1.0-1.5 mus. After semiconductor memory is rapidly developed to replace magnetic core memory as a main memory location, magnetic core memory can still be applied as a large-capacity expansion memory.

Drum memory, an external memory for magnetic recording. Because of its fast information access speed and stable and reliable operation, it is being replaced by disk memory, but it is still used as external memory for real-time process control computers and medium and large computers. In order to meet the needs of small and micro computers, subminiature magnetic drums have emerged, which are small, lightweight, highly reliable, and convenient to use.

Magnetic disk memory, an external memory for magnetic recording. It combines the advantages of drum and tape storage, i.e. its storage capacity is larger than that of drum, its access speed is faster than that of tape storage, and it can be stored off-line, so that the magnetic disk is widely used as large-capacity external storage in various computer systems. Magnetic disks are generally classified into two main categories, hard disks and floppy disk memories.

Hard disk memories are of a wide variety. The structure is divided into a replaceable type and a fixed type. The replaceable disk is replaceable and the fixed disk is fixed. The replaceable and fixed magnetic disks have both multi-disk combinations and single-chip structures, and are divided into fixed head types and movable head types. The fixed head type magnetic disk has a small capacity, a low recording density, a high access speed, and a high cost. The movable head type magnetic disk has a high recording density (up to 1000 to 6250 bits/inch) and thus a large capacity, but has a low access speed compared with a fixed head magnetic disk. The storage capacity of a magnetic disk product can reach several hundred megabytes with a bit density of 6250 bits per inch and a track density of 475 tracks per inch. The disk set of the multiple replaceable disk memory can be replaced, so that the disk set has large off-body capacity, large capacity and high speed, can store large-capacity information data, and is widely applied to an online information retrieval system and a database management system.

Example four:

the present disclosure also provides an electronic device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and when the processor executes the computer program, the steps of the adaptive blind detection method are implemented.

Fig. 8 is a schematic diagram of an internal structure of an electronic device in one embodiment. As shown in fig. 8, the electronic device includes a processor, a storage medium, a memory, and a network interface connected through a system bus. The storage medium of the computer device stores an operating system, a database and computer readable instructions, the database can store control information sequences, and the computer readable instructions when executed by the processor can enable the processor to realize an adaptive blind detection method. The processor of the electrical device is used to provide computing and control capabilities to support the operation of the entire computer device. The memory of the computer device may have stored therein computer readable instructions that, when executed by the processor, may cause the processor to perform a method of adaptive blind detection. The network interface of the computer device is used for connecting and communicating with the terminal. Those skilled in the art will appreciate that the architecture shown in fig. 8 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects apply, as particular computing devices may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.

The electronic device includes, but is not limited to, a smart phone, a computer, a tablet, a wearable smart device, an artificial smart device, a mobile power source, and the like.

The processor may be composed of an integrated circuit in some embodiments, for example, a single packaged integrated circuit, or may be composed of a plurality of integrated circuits packaged with the same or different functions, including one or more Central Processing Units (CPUs), microprocessors, digital Processing chips, graphics processors, and combinations of various control chips. The processor is a Control Unit of the electronic device, connects various components of the electronic device by using various interfaces and lines, and executes various functions and processes data of the electronic device by running or executing programs or modules (for example, executing remote data reading and writing programs, etc.) stored in the memory and calling data stored in the memory.

The bus may be a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. The bus is arranged to enable connected communication between the memory and at least one processor or the like.

Fig. 8 shows only an electronic device having components, and those skilled in the art will appreciate that the structure shown in fig. 8 does not constitute a limitation of the electronic device, and may include fewer or more components than those shown, or some components may be combined, or a different arrangement of components.

For example, although not shown, the electronic device may further include a power supply (such as a battery) for supplying power to each component, and preferably, the power supply may be logically connected to the at least one processor through a power management device, so that functions such as charge management, discharge management, and power consumption management are implemented through the power management device. The power supply may also include any component of one or more dc or ac power sources, recharging devices, power failure detection circuitry, power converters or inverters, power status indicators, and the like. The electronic device may further include various sensors, a bluetooth module, a Wi-Fi module, and the like, which are not described herein again.

Further, the electronic device may further include a network interface, and optionally, the network interface may include a wired interface and/or a wireless interface (such as a WI-FI interface, a bluetooth interface, etc.), which are generally used to establish a communication connection between the electronic device and other electronic devices.

Optionally, the electronic device may further comprise a user interface, which may be a Display (Display), an input unit (such as a Keyboard), and optionally a standard wired interface, a wireless interface. Alternatively, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode) touch device, or the like. The display, which may also be referred to as a display screen or display unit, is suitable, among other things, for displaying information processed in the electronic device and for displaying a visualized user interface.

Further, the computer usable storage medium may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function, and the like; the storage data area may store data created according to the use of the blockchain node, and the like.

In the embodiments provided in the present invention, it should be understood that the disclosed apparatus, device and method can be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the modules is only one logical functional division, and other divisions may be realized in practice.

The modules described as separate parts may or may not be physically separate, and parts displayed as modules may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment.

In addition, functional modules in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, or in a form of hardware plus a software functional module.

The embodiments of the present disclosure have been described above. However, these examples are for illustrative purposes only and are not intended to limit the scope of the present disclosure. The scope of the disclosure is defined by the appended claims and equivalents thereof. Various alternatives and modifications can be devised by those skilled in the art without departing from the scope of the present disclosure, and such alternatives and modifications are intended to be within the scope of the present disclosure.

Claims

1. An adaptive blind detection method, comprising:

initializing a current list size L of a successive elimination list decoding algorithm_nowInitial value of (2) and maximum list size L_max；

2. The method of claim 1, wherein after decoding all physical downlink control channels by using the consecutive elimination list decoding algorithm and performing cyclic redundancy check, the method further comprises:

3. The method of claim 2, wherein the current list size L is_nowIs increased by the current list size L_nowThe numerical value of (A) is doubled.

4. The method of any of claims 1-3, wherein initializing the current list size L of the consecutive elimination list decoding algorithm_nowThe initial values of (a) are specifically:

5. An adaptive blind detection device, comprising:

6. The apparatus of claim 5, further comprising:

7. The apparatus of claim 6, wherein the current list size L_nowIs increased by the current list size L_nowThe numerical value of (A) is doubled.

8. The apparatus of any of claims 5-7, wherein the initializing a current list size L of the consecutive elimination list decoding algorithm_nowThe initial values of (a) are specifically:

9. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the steps corresponding to the adaptive blind detection method as claimed in any one of claims 1 to 4 when executing the computer program.

10. A computer storage medium having computer program instructions stored thereon, wherein the program instructions, when executed by a processor, are adapted to perform the steps corresponding to the adaptive blind detection method of any of claims 1 to 4.