CN108242943A - The method and apparatus of precoding is used in communication - Google Patents
The method and apparatus of precoding is used in communication Download PDFInfo
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- H—ELECTRICITY
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- H04B7/00—Radio transmission systems, i.e. using radiation field
- H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
- H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
- H04B7/0413—MIMO systems
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Abstract
The method and apparatus that embodiment of the disclosure is related to being used for precoding in communication.The network equipment sends the pilot signal for utilizing the predetermined matrices for meeting RIP and being modeled precoding at least one terminal device.Terminal device persistently receives the pilot signal from the network equipment, and obtain angle domain channel response information using compressed sensing algorithm, based on the pilot signal having received, channel space correlation matrix is determined, and the information of channel space correlation matrix is sent to the network equipment based on angle domain channel response information.The network equipment receives the information of the channel space correlation matrix from all terminal devices, then stops pilot signal transmitted, and determine pre-coding matrix based on the information of channel space correlation matrix.It is possible thereby to realize determining for channel space correlation matrix with the use of minimum pilot signal, so as to save pilot signal overhead, system complexity is reduced, while quick determine mixing pre-coding scheme.
Description
Technical Field
Embodiments of the present disclosure relate to the field of wireless communications, and more particularly, to a method and apparatus for precoding.
Background
With the popularization of intelligent terminals and the development of mobile internet services, the fifth generation mobile communication technology (5G) puts higher requirements on data transmission rate. Multiple Input Multiple Output (MIMO) antenna arrays or "massive MIMO" technology are receiving increasing attention as a key technology for 5G.
The basic features of massive MIMO are: tens of antennas or even more than hundreds of antennas are configured in the coverage area of the base station, the number of the antennas is increased by more than one order of magnitude compared with 4 (or 8) antennas in a fourth generation mobile communication technology (4G) system, and the antennas are intensively arranged in a large-scale array mode. Therefore, the large-scale MIMO technology can more fully utilize the space dimensionality, greatly improve the spectrum efficiency and the power efficiency, and help operators to utilize the existing resources to the maximum extent.
However, due to the large number of antenna elements deployed in massive MIMO systems, conventional full digital precoding is no longer applicable as it incurs high hardware costs and implementation complexity that are hardly feasible. Hybrid precoding is currently a compelling solution to the cost and complexity issues.
Disclosure of Invention
In general, embodiments of the present disclosure provide methods and apparatus for precoding.
In one aspect of the disclosure, a method implemented at a network device for precoding is provided. The method comprises the following steps: transmitting a pilot signal to at least one terminal device, the pilot signal being analog precoded with a predetermined matrix satisfying a Restricted Isometry Property (RIP); receiving information of a channel spatial correlation matrix from the at least one terminal device, the channel spatial correlation matrix being determined using angle domain channel response information obtained based on the pilot signal by a compressed sensing algorithm; and determining a precoding matrix for hybrid precoding based on the information of the channel spatial correlation matrix.
In another aspect of the present disclosure, a method implemented at a terminal device for precoding is provided. The method comprises the following steps: receiving a pilot signal from a network device, the pilot signal being analog precoded with a predetermined matrix that satisfies the RIP; determining a channel space correlation matrix by utilizing angle domain channel response information obtained based on the received pilot frequency signal through a compressed sensing algorithm; and sending information of the channel space correlation matrix to the network equipment so that the network equipment can determine a precoding matrix for hybrid precoding.
In another aspect of the present disclosure, a network device is provided. The apparatus comprises: a transceiver configured to transmit a pilot signal to at least one terminal device, the pilot signal being analog precoded with a predetermined matrix satisfying a RIP, and to receive information of a channel spatial correlation matrix from the at least one terminal device, the channel spatial correlation matrix being determined with angle domain channel response information derived based on the pilot signal through a compressed sensing algorithm; and a controller configured to determine a precoding matrix for hybrid precoding based on the information of the channel spatial correlation matrix.
In another aspect of the disclosure, a terminal device is also provided. The apparatus comprises: a transceiver configured to receive a pilot signal from a network device, the pilot signal being analog precoded with a predetermined matrix satisfying a RIP, and to send information of a channel space correlation matrix to the network device for the network device to use to determine a precoding matrix for hybrid precoding; and a controller configured to determine the channel spatial correlation matrix using angle domain channel response information obtained based on the received pilot signal through a compressed sensing algorithm.
According to the scheme of the embodiment of the disclosure, the hybrid precoding scheme can be quickly determined, and the overhead and complexity of the pilot signal are greatly reduced.
It should be understood that the statements herein reciting aspects are not intended to limit the critical or essential features of the embodiments of the present disclosure, nor are they intended to limit the scope of the present disclosure. Other features of the present disclosure will become apparent from the following description.
Drawings
The above and other features, advantages and aspects of various embodiments of the present disclosure will become more apparent by referring to the following detailed description when taken in conjunction with the accompanying drawings. In the drawings, like or similar reference characters designate like or similar elements, and wherein:
fig. 1 illustrates a schematic diagram of a hybrid precoding architecture in which embodiments of the present disclosure may be implemented;
FIG. 2 illustrates a diagram of example communications and processing procedures for precoding in communications in accordance with an embodiment of the disclosure;
fig. 3 shows a flow diagram of a method for precoding implemented at a network device in accordance with an embodiment of the present disclosure;
FIG. 4 shows a flow diagram of a method for precoding implemented at a terminal device in accordance with an embodiment of the present disclosure;
FIG. 5 shows a graph comparing performance of a method according to an embodiment of the present disclosure with a conventional method;
FIG. 6 shows a graph of a performance analysis of a method for precoding in accordance with an embodiment of the present disclosure;
fig. 7 shows a block diagram of an apparatus for precoding implemented at a network device in accordance with an embodiment of the present disclosure;
fig. 8 shows a block diagram of an apparatus for precoding implemented at a terminal device according to an embodiment of the present disclosure; and
fig. 9 shows a block diagram of a device according to an embodiment of the present disclosure.
Detailed Description
Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While certain embodiments of the present disclosure have been illustrated in the accompanying drawings, it is to be understood that the present disclosure may be embodied in various forms and should not be construed as limited to the embodiments set forth herein, but rather are provided for a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the disclosure are for illustration purposes only and are not intended to limit the scope of the disclosure.
The term "network device" as used herein refers to a base station or other entity or node having a particular function in a communication network. A "base station" (BS) may represent a node B (NodeB or NB), an evolved node B (eNodeB or eNB), a Remote Radio Unit (RRU), a Radio Head (RH), a Remote Radio Head (RRH), a relay, or a low power node such as a pico base station, a femto base station, or the like. In the context of the present disclosure, the terms "network device" and "base station" may be used interchangeably for purposes of discussion.
The term "terminal equipment" or "user equipment" (UE) as used herein refers to any terminal equipment capable of wireless communication with a base station or with each other. As an example, the terminal device may include a Mobile Terminal (MT), a Subscriber Station (SS), a Portable Subscriber Station (PSS), a Mobile Station (MS), or an Access Terminal (AT), and the above-described devices in a vehicle. In the context of the present disclosure, the terms "terminal device" and "user equipment" may be used interchangeably for purposes of discussion convenience.
The terms "include" and variations thereof as used herein are inclusive and open-ended, i.e., "including but not limited to. The term "based on" is "based, at least in part, on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment". Relevant definitions for other terms will be given in the following description.
As mentioned earlier, hybrid precoding is a significant solution to the cost and complexity issues. Fig. 1 shows a schematic diagram of a hybrid precoding architecture 100 in which embodiments of the present disclosure may be implemented. As shown in fig. 1, the architecture 100 may include a baseband digital precoder 110, a plurality (4 shown in the figure, as an example) of Radio Frequency (RF) chains 120, an analog precoder 130, and an array 140 of a plurality (64 shown in the figure, as an example) of antennas. The data stream to be transmitted is mapped onto the respective subcarriers by performing a time-to-frequency domain conversion via the digital precoder 110. Each of the RF chains 120 is connected to a respective antenna in the antenna array 140 via an analog precoder 130 configured with a plurality of phase shifters. Thus, in the hybrid precoding architecture 100, the use of expensive RF links is reduced by employing inexpensive phase shifters.
However, determining the values of the hybrid precoding scheme and the large number of phase shifters is a huge challenge. One current approach is to perform beam scanning to determine analog domain beamforming. This process requires a large number of training beams to be expended in order to select the beam with the greatest received power among all beams as the analog domain beamforming. For massive MIMO systems with a large number of antenna elements, the number of training beams can be extremely large. Existing beam training procedures tend to transmit one training beam per OFDM symbol. For massive MIMO systems, this process tends to incur high pilot signal overhead because a large number of OFDM symbols need to be transmitted to convey a large number of training beams. Therefore, the beam alignment procedure will occupy a considerable amount of resources. This high overhead is even daunting in multi-user cells equipped with multiple antennas. In this case, the base station would need to allocate resources for each single user for the uplink beam scanning procedure.
As another approach, hybrid precoding may be determined based on a channel spatial correlation matrix, which is information based on instantaneous Channel State Information (CSI). However, this scheme also requires the transmission of a large number of OFDM symbols containing a large number of training beams, which is at least as large as the number of antenna elements. Thus, high pilot signal overhead and complexity may also be incurred.
In view of the above, the basic idea of the embodiments of the present disclosure is to estimate a power angular distribution (PAP) using a Compressed Sensing (CS) algorithm (or continuous CS algorithm) with sparsity of an angle-domain channel response instead of acquiring instantaneous CSI information, so that a channel spatial correlation matrix and then a hybrid precoding scheme can be quickly determined based on a small number of pilot signals without performing complete channel estimation (acquiring instantaneous CSI information). The determination of the channel space correlation matrix is realized by using the least pilot signals in a successive approximation mode, so that the pilot signal overhead is saved, and the system complexity is reduced. For ease of understanding, the following description is made in more detail in conjunction with FIG. 2.
Fig. 2 illustrates a schematic diagram of an example communication and processing procedure 200 for precoding in communication, in accordance with an embodiment of the present disclosure. The method for precoding according to the embodiments of the present disclosure may be implemented through interaction between a network device and a terminal device. In the following, a base station is taken as an example of a network device and a UE is taken as an example of a terminal device. It should be understood that embodiments of the present disclosure are applicable to other types of network devices and/or terminal devices, whether presently known or developed in the future.
As shown in fig. 2, the base station 210 transmits 211 a pilot signal to at least one UE 220 (only one UE is shown in the figure for simplicity). Accordingly, the UE 220 receives 212 the pilot signal.
According to an embodiment of the present disclosure, the pilot signal is analog precoded with a predetermined matrix that satisfies the RIP. The predetermined matrix is a training matrix pre-designed for applying the PAP estimate for analog pre-coding of the pilot signal.
In an embodiment of the present disclosure, the predetermined matrix may be a random matrix. For example, in one embodiment, the predetermined matrix may be generated as follows. First, independent and identically distributed complex random variables having a mean value of 0 and a variance of 1 are randomly selected from a gaussian function as matrix elements. Next, the norm of each matrix element can be made 1.
In an alternative embodiment, the predetermined matrix may be generated by: selecting matrix elements as a complex exponential sequence ejωWhere ω is randomly selected from the set [0,2 π). It should be understood that the predetermined matrix is not limited to the above listed forms, and may be any RIP-satisfying matrix known in the art or developed in the future. As will be described in detail later with respect to RIP. In an embodiment of the present disclosure, the base station may sequentially (one after another) transmit OFDM symbols for carrying pilot signals. In embodiments of the present disclosure, the base station may monitor the number of transmitted OFDM symbols and stop transmitting pilot signals if the number of transmitted OFDM symbols reaches a predetermined threshold. Thereby unnecessary pilot signal overhead can be reduced.
As shown in fig. 2, after receiving 212 the pilot signal, the UE 220 may determine 213 a channel spatial correlation matrix using angle domain channel response information derived based on the received pilot signal using a CS algorithm. In embodiments of the present disclosure, the predetermined matrix is known in advance to both the base station 210 and the UE 220. In an embodiment of the present disclosure, the at least one UE may include a plurality of UEs. Each UE estimates channel gains characterizing angle domain channel response information for pilot signals on all currently received OFDM symbols using a compressed sensing algorithm whenever one OFDM symbol is received until the estimated channel gains can be used to determine a channel spatial correlation matrix. The UE 220 then sends 214 information of the determined channel spatial correlation matrix to the base station 210.
Accordingly, the base station 210 receives 215 a channel spatial correlation matrix from the UE 220. In an embodiment of the present disclosure, the at least one UE may include a plurality of UEs. The base station 210 may determine whether channel spatial correlation matrices from all UEs are received and stop transmitting pilot signals if channel spatial correlation matrices from all UEs have been received. Thereby ensuring minimal pilot overhead. The base station 210 may then determine 216 a precoding matrix for hybrid precoding based on the received channel spatial correlation matrix. In an embodiment of the present disclosure, after the channel spatial correlation matrix is determined, the base station may estimate a precoding matrix for hybrid precoding. For the estimation process of the precoding matrix, it is not repeated here to avoid obscuring the present invention.
More specific example embodiments of the methods for precoding implemented at the base station and the UE, respectively, are described in detail below in conjunction with fig. 3 and 4, respectively. Fig. 3 shows a flow diagram of a method 300 for precoding implemented at a base station in accordance with an embodiment of the present disclosure. The method may be implemented, for example, at base station 210 of fig. 2. As shown in fig. 3, at 310, the base station 210 may transmit a pilot signal. According to an embodiment of the present disclosure, the base station 210 may sequentially transmit OFDM symbols carrying pilot signals.
At 320, the base station 210 may determine whether information of channel spatial correlation matrices from all UEs is received. In an embodiment of the present disclosure, the base station 210 may monitor the uplink data reception, for example, in real time or periodically, to determine whether information of the channel spatial correlation matrix from all UEs is received.
If it is determined at 320 that information of channel spatial correlation matrices from all UEs has not been received, the base station 210 may determine whether the number of transmitted OFDM symbols reaches a predetermined threshold at 330. In embodiments of the present disclosure, the base station 210 may monitor the number of transmitted OFDM symbols, e.g., in real-time or periodically, to determine whether the number of transmitted OFDM symbols reaches a predetermined threshold.
If it is determined at 330 that the number of transmitted OFDM symbols has not reached the predetermined threshold, then the pilot signal continues to be transmitted at 310. If it is determined at 330 that the number of transmitted OFDM symbols reaches a predetermined threshold, the transmission of the pilot signal is stopped at 340. Thereby, unnecessary pilot signal overhead is avoided.
On the other hand, if it is determined at 320 that information of channel spatial correlation matrices from all UEs is received, at 350, a precoding matrix for hybrid precoding is determined based on the received channel spatial correlation matrices. The processing of this step is similar to that described above in connection with 216 of fig. 2 and will not be described again here.
Fig. 4 illustrates a flow diagram of a method 400 implemented at a UE for precoding, in accordance with the present disclosure. The method may be implemented at the UE 220 of fig. 2. As shown in fig. 4, at 410, the UE 220 may receive a pilot signal. According to an embodiment of the present disclosure, the UE 220 may sequentially receive OFDM symbols carrying pilot signals.
At 420, the UE 220 determines a current channel gain (current channel gain vector) based on the pilot signals carried on the OFDM symbols received so far and the predetermined matrix. As mentioned above in connection with 213 of fig. 2, each UE may utilize a compressed sensing algorithm to estimate a channel gain vector characterizing the angle domain channel response information and the PAP for pilot signals on all OFDM symbols received so far whenever it receives one OFDM symbol, and then may determine a channel spatial correlation matrix based on the channel gain vector. This is obtained from the geometric channel model constructed by the present inventors and is explained below.
A downlink multi-user massive MIMO system is considered in embodiments of the present disclosure. For example, a base station BS and two single-antenna UEs may be included in the system. For example, the BS may include NRFAn RF link, NRFOne RF link is connected with NtA transmitting antenna, assuming the NtThe transmitting antennas are Uniform Linear Arrays (ULAs) and the NtThe transmit antennas are each spaced apart, for example, by one-half wavelength.
For OFDM systems, the signal s is passed through a precoding vector before being transmittedAnd (4) weighting. The precoding vector is a baseband digital precoding vectorAnd simulating precoding vectorsCombinations of (a) and (b). The signal r received at the k sub-carrierkCan be written as:
wherein h represents NtX 1 channel vector, e denotes gaussian white noise.
A geometric channel model represented by equation (1) is considered in the embodiments of the present disclosure. In the geometric channel model, the channel vector can be written as:
wherein, αlThe complex array gain of the L-th propagation path is represented, and L is the total number of propagation paths.A vector of the response of the array is represented,is the direction of departure of the path in the azimuth plane (DoD). For a ULA with N antenna elements, the array response vectorHaving the form:
where k is 2 pi/λ and d is the distance between the antenna elements.
Suppose thatRepresenting a Discrete Fourier Transform (DFT) matrix, WlIs the ith column vector. Here, N in the azimuth plane may be represented using a column vector in WtThe number of different dods, i.e.,suppose thatThe channel vector can be written as:
wherein 1/N is utilizedtQuantizes the angular domain, and h is NtN on each DoDtNote that vector α is sparse because the number of strong reflection paths is limited.
In embodiments of the present disclosure, signals from different RF chains occupy orthogonal subcarriers. Thus, the signal on a single subcarrier is mapped to only one RF chain. Thus, the digital precoding vector f on each subcarrierBB，kDesigned to be all 0's but 1's at the index corresponding to the mapped RF link, i.e., fBB，k＝[0，...，0，1，0，...，0]T. Then the precoding vector fkIs at FRFA column vector f selected fromRFWhich indicates the value of the phase shifter connected to the single RF chain. The total bandwidth is divided equally into NRFAn RF link. Thus, N may be transmitted per OFDM symbolRFA number of training beams, such that the number of training beams is proportional to the number of RF chains. Suppose thatIs FRFN in (1)RFA column vector, then for each OFDM symbol, the received signal can be written as:
wherein,n＝1，2，...，NRFrepresenting the set of subcarriers in which the same precoding vector is applied.
For simplicity, assume that signal s is one unit on all subcarriers, andrepresenting the total number of subcarriers in the set of subcarriers. Above generalThe received signal may be composedVector number:
whereinIf m OFDM symbols are received, the received signal and the transmitted training beam will increase by a factor of m. Each received signal vectorHas a size of mNRFX 1. Suppose thatAs a stacked precoding vector, then the received signal vector can be written as:
wherein F ═ FRF，1；FRF，2；...；FRF，m]And F isRF，iI 1, 2.. m is a precoding matrix transmitted in the ith OFDM symbol.
And then can be from rnThe complex gain vector α is estimated using the appropriate training beam matrix F when the channel gain vectors over all dods are obtained, the channel spatial correlation matrix R can be estimated as follows:
whereinIs derived from the received signal vector rnThe estimated complex gain vector is also referred to herein as a channel gain vector. The channel gain vector may characterize the angle domain channel response information of the received signal, so R retains the angle domain channel response information and may be used to accurately generate precoding matrices for analog precoding.
Since channel gain vector α is sparse, the CS algorithm may be utilized to use only the ratio N in embodiments of the present disclosuretMuch fewer received signals to quickly estimate α ideally, the number of training beams (mN)RF) Not less than NtTime recovery vector α the received signal vector in equation (7) may be further written as:
wherein is mNRF×NtMatrix a ═ FTW. assume that there are only q major non-zero values in vector α, which is considered q-sparseRFRecovering the vector α, wherein cqlog (N) is present in the received signalt/q)＜mNRF＜＜NtAnd c > 0.
Matrix a needs to be carefully designed to recover the high-dimensional vector α from the low-dimensional vector r matrix a is sufficient prerequisite for preserving the non-zero information of the q-sparse vector α and achieving reconstruction is to satisfy RIP, if equation (10) below is satisfied, matrix a is said to satisfy RIP.
Where any vector v has up to 2q non-zero elements and the constant epsilon > 0.
Based on this geometric channel model, the predetermined matrix F for analog precoding of pilot signals is thus designed in embodiments of the present disclosure to satisfy RIP, as described previously in connection with 210 of fig. 2, to be applied to transmission of pilot signals on the base station side and to determine channel gain vectors characterizing angle domain channel response information based on the CS algorithm on the UE side to estimate the channel spatial correlation matrix.
Then, the predetermined matrix F multiplied by the DFT matrix W may also satisfy rip, and thus, the q-sparse vector α may be estimated by the following equation (11):
where μ is tied to noise level and is typically chosen as μ > | e | | computationally2. The estimated vector can then be utilizedTo estimate the channel spatial correlation matrix from equation (8) above.
With continued reference to fig. 4, at 430, the UE 220 may determine whether a change between a current channel gain vector relative to a previous channel gain vector determined for all previously received OFDM symbols is below a predetermined threshold. For example, it is determined whether the following expression (12) holds:
whereinWhich represents the current channel gain vector and is,representing the previous channel gain vector and tau represents the predetermined threshold.
If it is determined at 430 that the change between the current channel gain vector and the previous channel gain vector is below a predetermined threshold, at 440, a channel spatial correlation matrix is determined based on the current channel gain vector. In an embodiment of the present disclosure, in case it is determined that the change between the current channel gain vector and the previous channel gain vector is below the predetermined threshold, the UE may stop to continue estimating the channel gain vector while determining the channel spatial correlation matrix based on the current channel gain vector, e.g., based on equation (8) above.
If it is determined at 430 that the change between the current channel gain vector and the previous channel gain vector is greater than the predetermined threshold, then reception of pilot signals for the next OFDM symbol continues at 410 and subsequent channel gain vectors are determined using pilot signals on all OFDM symbols received so far for comparison with the current channel gain vector until the condition at 430 is satisfied. Therefore, the determination of the channel space correlation matrix is realized by using the least pilot signals in a successive approximation mode, so that the pilot signal overhead is saved, and the system complexity is reduced.
After determining the channel spatial correlation matrix, at 450, the UE 220 may feed back the channel spatial correlation matrix to the base station for use by the base station in determining a precoding matrix for hybrid precoding. The processing of this step is similar to that described above in connection with 216 of fig. 2 and will not be described again here.
A method for precoding according to an embodiment of the present disclosure has been described so far. The method provides a sequential training process, on one hand, the minimum number of OFDM symbols can be transmitted, so that the pilot signal overhead is minimized, and on the other hand, the hybrid precoding matrix can be quickly determined, so that the system complexity is reduced.
Fig. 5 shows a graph 500 of a performance comparison between a method according to an embodiment of the present disclosure and a conventional method. As shown in fig. 5, 510 represents the performance of the legacy method based on true CSI, 520 represents the performance of the legacy method based on instantaneous CSI, and 530 represents the performance of the method (CS-based) based on an embodiment of the present disclosure. Wherein both the conventional method and the method of the embodiments of the present disclosure employ the same hybrid precoding algorithm based on the channel spatial correlation matrix. It can be seen that the method of the disclosed embodiments can achieve similar capacity as the conventional method. The method according to the embodiments of the present disclosure requires only 5 OFDM symbols, which include 20 training beams, whereas in the conventional method 16 OFDM symbols are required to transmit 64 training beams. Therefore, according to the method disclosed by the embodiment of the disclosure, the number of required training beams can be obviously reduced, so that the overhead of pilot signals is greatly reduced.
Furthermore, the number of training beams required to use the method of embodiments of the present disclosure depends on the channel conditions, i.e., the sparsity of the power angular distribution. Fig. 6 shows a graph 600 of a performance analysis of a method for precoding according to an embodiment of the present disclosure. There is shown a performance curve with precoding determined by the method of an embodiment of the present disclosure in the case of receiving a different number of OFDM symbols. With a signal-to-noise ratio of 15 dB. As shown in fig. 6, performance becomes substantially stable from the 4 th OFDM symbol. This indicates that the angle domain channel response information can be recovered with 4 OFDM symbols (16 training beams). According to an embodiment of the present disclosure, the number of OFDM symbols may be smaller for LoS scenarios or channels with strong reflected paths.
Corresponding to the method for precoding according to the embodiment of the present disclosure, the embodiment of the present disclosure also provides a corresponding apparatus for precoding. This is described in detail below in conjunction with fig. 7 and 8.
Fig. 7 shows a block diagram of an apparatus 700 for precoding implemented at a base station according to an embodiment of the present disclosure. It should be understood that apparatus 700 may be implemented at a base station, such as base station 210 of fig. 2. Alternatively, the apparatus 700 may be the base station itself.
As shown in fig. 7, the apparatus 700 may include a first transmitting unit 710, a first receiving unit 720, and a first determining unit 730. The first transmitting unit 710 may be configured to transmit pilot signals, which are analog precoded with a predetermined matrix satisfying the RIP, to at least one UE. The first receiving unit 720 may be configured to receive information of channel spatial correlation matrices from at least one UE, the channel spatial correlation matrices being respectively determined based on angle domain channel response information obtained by the UE using a compressed sensing algorithm based on pilot signals. The first determining unit 730 may be configured to determine a precoding matrix for hybrid precoding based on information of the channel spatial correlation matrix.
According to an embodiment of the present disclosure, the predetermined matrix is generated by: randomly selecting independent and uniformly distributed complex random variables from a Gaussian function as matrix elements, wherein the mean value of the complex random variables is 0 and the variance is 1; and making the norm of each matrix element 1. In an alternative embodiment, the predetermined matrix is generated by: selecting matrix elements as a complex exponential sequence ejωWhere ω is an arc value randomly selected from the set [0,2 π).
According to an embodiment of the present disclosure, the at least one UE may include a plurality of UEs. In this embodiment, the first determining unit 730 may be further configured to: determining whether information of a channel spatial correlation matrix from each of the plurality of UEs is received, and determining the precoding matrix based on the information of the channel spatial correlation matrix in response to receiving the information of the channel spatial correlation matrix from each of the plurality of UEs.
According to an embodiment of the present disclosure, the apparatus 700 may further comprise a monitoring unit (not shown in the figures) configured to: monitoring the number of OFDM symbols transmitted to carry the pilot signal; and in response to the number of transmitted OFDM symbols reaching a predetermined threshold, ceasing to transmit the pilot signal.
Fig. 8 shows a block diagram of an apparatus 800 for precoding implemented at a UE in accordance with an embodiment of the present disclosure. It should be understood that apparatus 800 may be implemented at a UE, such as UE 220 of fig. 2. Alternatively, the apparatus 800 may be the UE itself.
As shown in fig. 8, the apparatus 800 may include a second receiving unit 810, a second determining unit 820, and a second transmitting unit 830. The second receiving unit 810 may be configured to receive a pilot signal from a base station, the pilot signal being analog-precoded with a predetermined matrix satisfying the RIP. The second determining unit 820 may be configured to determine a channel spatial correlation matrix based on angle domain channel response information obtained based on the received pilot signals using a compressed sensing algorithm. The second transmitting unit 830 may be configured to transmit information of the channel spatial correlation matrix to the base station for the base station to use for determining a precoding matrix for hybrid precoding.
According to an embodiment of the present disclosure, the predetermined matrix is generated by: randomly selecting independent and uniformly distributed complex random variables from a Gaussian function as matrix elements, wherein the mean value of the complex random variables is 0 and the variance is 1; and making the norm of each matrix element 1. In an alternative embodiment, the predetermined matrix is generated by: selecting matrix elements as a complex exponential sequence ejωWhere ω is fromSet [0,2 π) randomly selected arc values.
According to an embodiment of the present disclosure, the second determining unit 820 may be further configured to: determining a current channel gain vector based on pilot signals carried on OFDM symbols received so far and a predetermined matrix; determining a change in a current channel gain vector relative to a previous channel gain vector, the previous channel gain vector being determined based on pilot signals carried on previously received OFDM symbols and a predetermined matrix; and in response to the change being below a predetermined threshold, determining a channel spatial correlation matrix based on a current channel gain vector.
According to an embodiment of the present disclosure, the second determining unit 820 may be further configured to: receiving a subsequent OFDM symbol in response to the change being greater than a predetermined threshold; and determining a subsequent channel gain vector for comparison with the current channel gain vector based on the pilot signals carried on the received OFDM symbols and the predetermined matrix.
It should be understood that each unit recited in the apparatuses 700 and 800 corresponds to each action in the methods 300 to 400 described with reference to fig. 3 to 4, respectively. Moreover, the operations and features of the apparatuses 700, 800 and the units included therein all correspond to the operations and features described above in connection with fig. 3 to 4 and have the same effects, and detailed details are not repeated.
Fig. 9 illustrates a block diagram of a device 900 suitable for implementing embodiments of the present disclosure. Apparatus 900 may be used to implement a base station (e.g., base station 210 of fig. 2) and/or to implement a UE (e.g., base station 220 of fig. 2).
As shown, the device 900 includes a controller 910. The controller 910 controls the operation and functions of the device 900. For example, in certain embodiments, the controller 910 may perform various operations by way of instructions 930 stored in a memory 920 coupled thereto. The memory 920 may be of any suitable type suitable to the local technical environment and may be implemented using any suitable data storage technology, including but not limited to semiconductor-based memory devices, magnetic memory devices and systems, optical memory devices and systems. Although only a single memory unit is illustrated in FIG. 9, there may be multiple physically distinct memory units within device 900.
The controller 910 may be of any suitable type suitable to the local technical environment, and may include, but is not limited to, at least one of a general purpose computer, a special purpose computer, a microcontroller, a digital signal controller (DSP), and a controller-based multi-core controller architecture. The device 900 may also include a plurality of controllers 910. The controller 910 is coupled to a transceiver 940, and the transceiver 940 may enable receiving and transmitting information by way of at least one antenna 950 and/or other components. Note that the transceiver 940 may be a separate device or may include separate devices for transmitting and receiving, respectively.
When the device 900 is acting as a base station, the controller 910 and the transceiver 940 may operate in conjunction to implement the method 300 described above with reference to fig. 3. When the device 900 is acting as a UE, the controller 910 and transceiver 940 may operate in conjunction, e.g., under the control of instructions 930 in memory 920, to implement the method 400 described above with reference to fig. 4. For example, the transceiver 940 may perform operations related to the reception and/or transmission of data/information, while the controller 910 performs or triggers processing, computation, and/or other operations on the data. All of the features described above with reference to fig. 2-4 apply to the apparatus 900 and are not described in detail herein.
In general, the various example embodiments of this disclosure may be implemented in hardware or special purpose circuits, software, logic or any combination thereof. Certain aspects may be implemented in hardware, while other aspects may be implemented in firmware or software which may be executed by a controller, microprocessor or other computing device. While aspects of embodiments of the disclosure have been illustrated or described as block diagrams, flow charts, or using some other pictorial representation, it is well understood that the blocks, apparatus, systems, techniques or methods described herein may be implemented in, as non-limiting examples, hardware, software, firmware, special purpose circuits or logic, general purpose hardware or controller or other computing devices, or some combination thereof. Examples of hardware devices that may be used to implement embodiments of the present disclosure include, but are not limited to: field Programmable Gate Arrays (FPGAs), Application Specific Integrated Circuits (ASICs), Application Specific Standards (ASSPs), systems on a chip (SOCs), Complex Programmable Logic Devices (CPLDs), and the like.
By way of example, embodiments of the disclosure may be described in the context of machine-executable instructions, such as those included in program modules, being executed in a device on a target real or virtual processor. Generally, program modules include routines, programs, libraries, objects, classes, components, data structures, etc. that perform particular tasks or implement particular abstract data types. In various embodiments, the functionality of the program modules may be combined or divided between program modules as described. Machine-executable instructions for program modules may be executed within local or distributed devices. In a distributed facility, program modules may be located in both local and remote memory storage media.
Computer program code for implementing the methods of the present disclosure may be written in one or more programming languages. These computer program codes may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the program codes, when executed by the computer or other programmable data processing apparatus, cause the functions/acts specified in the flowchart and/or block diagram block or blocks to be performed. The program code may execute entirely on the computer, partly on the computer, as a stand-alone software package, partly on the computer and partly on a remote computer or entirely on the remote computer or server.
In the context of this disclosure, a machine-readable medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination thereof. More detailed examples of a machine-readable storage medium include an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical storage device, a magnetic storage device, or any suitable combination thereof.
Additionally, while operations are depicted in a particular order, this should not be understood as requiring that such operations be performed in the particular order shown or in sequential order, or that all illustrated operations be performed, to achieve desirable results. In some cases, multitasking or parallel processing may be beneficial. Likewise, while the above discussion contains certain specific implementation details, this should not be construed as limiting the scope of any invention or claims, but rather as describing particular embodiments that may be directed to particular inventions. Certain features that are described in this specification in the context of separate embodiments can also be implemented in combination in a single embodiment. Conversely, various features that are described in the context of a single embodiment can also be implemented in multiple embodiments separately or in any suitable subcombination.
Although the subject matter has been described in language specific to structural features and/or methodological acts, it is to be understood that the subject matter defined in the appended claims is not limited to the specific features or acts described above. Rather, the specific features and acts described above are disclosed as example forms of implementing the claims.
Claims (20)
1. A method implemented at a network device for precoding, comprising:
transmitting a pilot signal to at least one terminal device, the pilot signal being analog precoded with a predetermined matrix satisfying a Restricted Isometry Property (RIP);
receiving information of a channel spatial correlation matrix from the at least one terminal device, the channel spatial correlation matrix being determined using angle domain channel response information obtained based on the pilot signal by a compressed sensing algorithm; and
and determining a precoding matrix for hybrid precoding based on the information of the channel space correlation matrix.
2. The method of claim 1, wherein the at least one terminal device comprises a plurality of terminal devices, and the determining a precoding matrix comprises:
determining whether information of the channel spatial correlation matrix is received from each of the plurality of terminal devices; and
in response to determining that information of the channel spatial correlation matrix has been received from each of the plurality of terminal devices, determining the precoding matrix based on the information of the channel spatial correlation matrix.
3. The method of claim 1, further comprising:
monitoring a number of Orthogonal Frequency Division Multiplexing (OFDM) symbols transmitted to carry the pilot signal; and
ceasing to transmit the pilot signal in response to the number of transmitted OFDM symbols reaching a predetermined threshold.
4. The method of claim 1, further comprising generating the predetermined matrix as follows:
randomly selecting independent and uniformly distributed complex random variables from a Gaussian function as matrix elements, wherein the mean value of the complex random variables is 0 and the variance is 1; and
let the norm of each matrix element be 1.
5. The method of claim 1, further comprising generating the predetermined matrix as follows:
selecting matrix elements as a complex exponential sequence ejωWhere ω represents a randomly selected radian value from the set [0,2 π).
6. A method implemented at a terminal device for precoding, comprising:
receiving a pilot signal from a network device, the pilot signal being analog precoded with a predetermined matrix that satisfies a Restricted Isometry Property (RIP);
determining a channel correlation matrix by using angle domain channel response information obtained based on the received pilot signals through a compressed sensing algorithm; and
and sending the information of the channel space correlation matrix to the network equipment so that the network equipment can determine a precoding matrix for hybrid precoding.
7. The method of claim 6, wherein the determining a channel spatial correlation matrix comprises:
determining a current channel gain based on the pilot signals carried on Orthogonal Frequency Division Multiplexing (OFDM) symbols received so far and the predetermined matrix; and
determining a change between the current channel gain relative to a previous channel gain determined based on the pilot signals carried on previously received OFDM symbols and the predetermined matrix;
determining the channel spatial correlation matrix based on the current channel gain in response to the change being below a predetermined threshold.
8. The method of claim 7, further comprising:
receiving a subsequent OFDM symbol in response to the change being greater than the predetermined threshold; and
determining a subsequent channel gain for comparison with the current channel gain based on the pilot signals carried on subsequent received OFDM symbols and the OFDM symbols received so far and the predetermined matrix.
9. The method of claim 6, further comprising generating the predetermined matrix as follows:
randomly selecting independent and identically distributed complex random variables as matrix elements from a Gaussian function, wherein the mean value of the complex random variables is 0 and the variance is 1; and
let the norm of each matrix element be 1.
10. The method of claim 6, further comprising generating the predetermined matrix as follows:
selecting matrix elements as a complex exponential sequence ejωWhere ω represents a randomly selected radian value from the set [0,2 π).
11. A network device, comprising:
a transceiver configured to transmit a pilot signal to at least one terminal device, the pilot signal being analog precoded with a predetermined matrix satisfying a Restricted Isometry Property (RIP), and to receive information from the at least one terminal device of a channel spatial correlation matrix determined with angle domain channel response information derived based on the pilot signal by a compressed sensing algorithm; and
a controller configured to determine a precoding matrix for hybrid precoding based on the information of the channel spatial correlation matrix.
12. The device of claim 11, wherein the at least one terminal device comprises a plurality of terminal devices, and the controller is further configured to:
determining whether information of the channel spatial correlation matrix is received from each of the at least one terminal device; and
in response to determining that information of the channel spatial correlation matrix from each of the plurality of terminal devices has been received, determining the precoding matrix based on the channel spatial correlation matrix.
13. The apparatus of claim 11, wherein the controller is further configured to:
monitoring a number of Orthogonal Frequency Division Multiplexing (OFDM) symbols transmitted to carry the pilot signal; and
ceasing to transmit the pilot signal in response to the number of transmitted OFDM symbols reaching a predetermined threshold.
14. The apparatus of claim 11, wherein the predetermined matrix is generated as follows:
randomly selecting independent and uniformly distributed complex random variables from a Gaussian function as matrix elements, wherein the mean value of the complex random variables is 0 and the variance is 1; and
let the norm of each matrix element be 1.
15. The apparatus of claim 11, wherein the predetermined matrix is generated as follows:
selecting matrix elements as a complex exponential sequence ejωWhere ω represents a randomly selected radian value from the set [0,2 π).
16. A terminal device, comprising:
a transceiver configured to receive a pilot signal from a network device, the pilot signal being analog precoded with a predetermined matrix satisfying a Restricted Isometry Property (RIP), and to send information of a channel space correlation matrix to the network device for use by the network device in determining a precoding matrix for hybrid precoding; and
a controller configured to determine the channel spatial correlation matrix using angle domain channel response information obtained based on the received pilot signals through a compressed sensing algorithm.
17. The apparatus of claim 16, wherein the controller is further configured to:
determining a current channel gain based on the pilot signals carried on Orthogonal Frequency Division Multiplexing (OFDM) symbols received so far and the predetermined matrix;
determining a change in the current channel gain relative to a previous channel gain determined based on the pilot signals carried on previously received OFDM symbols and the predetermined matrix; and
determining the channel spatial correlation matrix based on the current channel gain in response to the change being below a predetermined threshold.
18. The apparatus of claim 17, wherein the controller is further configured to:
receiving a subsequent OFDM symbol in response to the change being greater than the predetermined threshold; and
determining a subsequent channel gain for comparison with the current channel gain based on the pilot signals carried on subsequent received OFDM symbols and the OFDM symbols received so far and the predetermined matrix.
19. The apparatus of claim 16, wherein the predetermined matrix is generated as follows:
randomly selecting independent and identically distributed complex random variables as matrix elements from a Gaussian function, wherein the mean value of the complex random variables is 0 and the variance is 1; and
let the norm of each matrix element be 1.
20. The apparatus of claim 16, wherein the predetermined matrix is generated as follows:
selecting matrix elements as a complex exponential sequence ejωWhere ω represents a randomly selected radian value from the set [0,2 π).
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