Cooperative base station selection method and user terminal based on spatial correlation

Abstract

The present invention discloses a method for selecting a collaborative base station based on spatial correlation and a user terminal. The method is applied to a user terminal, and the method includes: determining the correlation coefficient between the user terminal and each base station according to the channel information between the user terminal and the base station; determining at least one collaborative base station for serving the user terminal from all base stations according to the correlation coefficient and the large-scale fading coefficient, and obtaining a base station cluster of the user terminal. According to the method provided by the present invention, the collaborative base station for serving the user terminal is determined by jointly determining the large-scale fading coefficient and the correlation coefficient between the base station and the user terminal, and the collaborative base station can be determined by more comprehensive factors, thereby improving the transmission performance and transmission quality of the base station cluster.

Description

Technical Field

[0001] The present invention belongs to the field of communication technology, and in particular relates to a method and device for selecting a collaborative base station based on spatial correlation. Background Art

[0002] In order to improve network throughput to a greater extent, network densification (Ultra Dense Network, UDN) has received great attention in 5G wireless communications. Under the existing cellular network architecture with centralized multiple-input multiple-output (MIMO) as the core technology, the growing number of smart devices and the explosive growth of wireless data traffic demand have put the performance of communication networks under severe test, and network densification can alleviate such problems to a certain extent. However, the reduction in cell size leads to a sharp increase in the number of users at the cell edge, that is, the interference area between base stations becomes larger, especially the performance of users at the cell edge is significantly deteriorated, making it difficult to achieve the expected network throughput improvement value. In order to solve this problem, distributed MIMO represented by coordinated multiple points (CoMP) and cell-free systems has been proposed in recent years. Compared with traditional massive MIMO, distributed MIMO no longer uses a single base station to serve all users in a cell, but uses a group of base stations / access points (AP) to collaboratively serve one or a group of user equipment (UE). This method can effectively control the interference between multiple cells in a local area, especially at the cell edge, thereby significantly improving the performance of users at the cell edge and improving spectrum efficiency. It is considered to be one of the technical solutions for the future sixth-generation mobile communication system.

[0003] In a distributed MIMO system, due to the limited computing power and capacity of the base station, it is unable to undertake the signal processing and channel state information (CSI) estimation tasks for all users in the scene, and the fronthaul link capacity is limited, so it is necessary to establish a cooperative cluster to limit the number of users served by the base station. On the other hand, due to the path loss during transmission, the signal strength of some base stations is not enough for transmission when they reach the user. Moreover, when the total transmission power can guarantee good signal quality, the introduction of additional cooperative base stations may even reduce the transmission performance. In short, whether from the perspective of the base station or the user, establishing a suitable cooperative cluster, that is, the selection of cooperative base stations, can effectively improve resource utilization and transmission performance.

[0004] As for the collaborative base station selection technology, it has developed from CoMP to the present. According to the selection update method, it can be divided into static selection, semi-dynamic selection and dynamic selection. The static selection method is less complicated and has less signaling overhead, but this method cannot respond to changes in network nodes or user locations, so the performance gain is limited. Semi-dynamic selection is an enhanced version of static selection, in which multiple static selections are formed and dynamically used to increase potential benefits, but this method still cannot truly respond to dynamic changes in the network. The dynamic selection method was developed to respond to changes in network and user mobility, i.e. new sites, sleeping cells, load changes, etc. Although this method increases the complexity of scheduling and beamforming design, it can effectively reduce inter-cluster interference by flexibly adjusting the collaborative cluster configuration and show the best performance.

[0005] Although the dynamic selection method increases the complexity of scheduling and beamforming design, it can effectively reduce inter-cluster interference by flexibly adjusting the cooperative cluster configuration and show the best performance. For frequency division duplexing (FDD) systems, cooperative base station selection based on received power and objective function is difficult to apply directly because it relies on complete channel information. Therefore, FDD systems usually use base station selection methods based on large-scale fading coefficients.

[0006] However, in FDD systems, the research on base station selection generally adopts codebook technology and mostly relies on large-scale fading coefficients to select base stations, taking fewer factors into consideration, which leads to lower transmission performance and quality of the system. Summary of the invention

[0007] The embodiment of the present invention provides a method for selecting a cooperative base station based on spatial correlation and a user terminal, which can solve the problem of low transmission performance and quality of the system.

[0008] In a first aspect, an embodiment of the present invention provides a method for selecting a cooperative base station based on spatial correlation, the method being applied to a user terminal, and the method comprising:

[0009] Determine a correlation coefficient between the user terminal and each base station according to channel information between the user terminal and the base station;

[0010] At least one cooperative base station for serving the user terminal is determined from all base stations according to the correlation coefficient and the large-scale fading coefficient, so as to obtain a base station cluster of the user terminal.

[0011] In a possible implementation manner of the first aspect, a downlink channel between a user terminal and each base station can be determined based on channel information; the downlink channel is decomposed to obtain a singular value matrix; and the ratio of the maximum value to the minimum value in the singular value matrix is ​​determined as the correlation coefficient.

[0012] In a possible implementation manner of the first aspect, all base stations can be arranged in ascending order according to the large-scale fading coefficient between the base station and the user terminal to obtain the first first sequence; determine whether the difference in large-scale fading coefficient between the second base station and the first base station in the h-th first sequence is less than the large-scale fading coefficient threshold, and whether the correlation coefficient difference is greater than the spatial correlation threshold; if the difference in large-scale fading coefficient between the second base station and the first base station in the h-th first sequence is less than the large-scale fading coefficient threshold, and the correlation coefficient difference is greater than the spatial correlation threshold, then the second base station in the h-th first sequence is determined as a collaborative base station and added to the base station cluster, and the second base station in the h-th first sequence is deleted to obtain the h+1-th first sequence; otherwise, the first base station in the h-th first sequence is determined as a collaborative base station and added to the base station cluster, and the first base station in the h-th first sequence is deleted to obtain the h+1-th first sequence.

[0013] Exemplarily, the magnitude of the large-scale fading coefficient is proportional to the distance between the base station and the user terminal.

[0014] Exemplarily, h=1, 2...NUM, where NUM is the maximum number of cooperative base stations in the base station cluster.

[0015] In a possible implementation of the first aspect, a precoding matrix is ​​also obtained when the downlink channel is decomposed. The service effect of the base station cluster can also be evaluated according to the precoding matrix between each cooperative base station and the user terminal, and the spectrum efficiency of the base station cluster serving the user terminal can be determined; and the cooperative base stations in the base station cluster can be adjusted according to the spectrum efficiency.

[0016] In a possible implementation method of the first aspect, the precoding matrix between the ith collaborative base station and the gth service user terminal can be quantized based on a standard codebook to obtain a quantized precoding matrix between the ith collaborative base station and the gth service user terminal; the global quantized precoding matrix of the ith collaborative base station is determined based on the quantized precoding matrix between the ith collaborative base station and the gth service user terminal; a precoding operation is performed on the global quantized precoding matrix of the ith collaborative base station to obtain the global precoding matrix of the ith collaborative base station; and the spectrum efficiency of the base station cluster serving the user terminal is determined based on the downlink channel between the user terminal and each collaborative base station, and the global quantized precoding matrix of all collaborative base stations.

[0017] Exemplarily, i and g are both positive integers greater than or equal to 1.

[0018] Exemplarily, the served user terminal is a user terminal served by the i-th cooperative base station, and the served user terminal includes the above-mentioned user terminal.

[0019] In a second aspect, an embodiment of the present invention provides a user terminal, wherein the user terminal includes a processing unit; the processing unit is used to:

[0020] Determine a correlation coefficient between the user terminal and each base station according to channel information between the user terminal and the base station;

[0021] At least one cooperative base station for serving the user terminal is determined from all base stations according to the correlation coefficient and the large-scale fading coefficient, so as to obtain a base station cluster of the user terminal.

[0022] In a possible implementation of the second aspect, the processing unit can be specifically used to determine the downlink channel between the user terminal and each base station based on the channel information; decompose the downlink channel to obtain a singular value matrix; and determine the ratio of the maximum value to the minimum value in the singular value matrix as the correlation coefficient.

[0023] In a possible implementation manner of the second aspect, the processing unit can be specifically used to arrange all base stations in ascending order according to the large-scale fading coefficient between the base station and the user terminal to obtain the first first sequence; determine whether the difference in large-scale fading coefficients between the second base station and the first base station in the h-th first sequence is less than the large-scale fading coefficient threshold, and whether the correlation coefficient difference is greater than the spatial correlation threshold; if the difference in large-scale fading coefficients between the second base station and the first base station in the h-th first sequence is less than the large-scale fading coefficient threshold, and the correlation coefficient difference is greater than the spatial correlation threshold, then the second base station in the h-th first sequence is determined as a collaborative base station and added to the base station cluster, and the second base station in the h-th first sequence is deleted to obtain the h+1-th first sequence; otherwise, the first base station in the h-th first sequence is determined as a collaborative base station and added to the base station cluster, and the first base station in the h-th first sequence is deleted to obtain the h+1-th first sequence.

[0024] Exemplarily, the magnitude of the large-scale fading coefficient is proportional to the distance between the base station and the user terminal.

[0025] Exemplarily, h=1, 2...NUM, where NUM is the maximum number of cooperative base stations in the base station cluster.

[0026] In a possible implementation of the second aspect, the processing unit further obtains a precoding matrix when decomposing the downlink channel. The processing unit can also be used to evaluate the service effect of the base station cluster according to the precoding matrix between each cooperative base station and the user terminal, determine the spectrum efficiency of the base station cluster serving the user terminal, and adjust the cooperative base stations in the base station cluster according to the spectrum efficiency.

[0027] In a possible implementation of the second aspect, the processing unit can be specifically used to quantize the precoding matrix between the ith collaborative base station and the gth service user terminal through a standard code book to obtain a quantized precoding matrix between the ith collaborative base station and the gth service user terminal; determine the global quantized precoding matrix of the ith collaborative base station based on the quantized precoding matrix between the ith collaborative base station and the gth service user terminal; perform a precoding operation on the global quantized precoding matrix of the ith collaborative base station to obtain the global precoding matrix of the ith collaborative base station; determine the spectrum efficiency of the base station cluster serving the user terminal based on the downlink channel between the user terminal and each collaborative base station, and the global quantized precoding matrix of all collaborative base stations.

[0028] Exemplarily, i and g are both positive integers greater than or equal to 1.

[0029] Exemplarily, the served user terminal is a user terminal served by the i-th cooperative base station, and the served user terminal includes the above-mentioned user terminal.

[0030] The beneficial effects of the embodiments of the present invention compared with the prior art are: according to the method provided by the present invention, the collaborative base station used to serve the user terminal is jointly determined by the large-scale fading coefficient and correlation coefficient between the base station and the user terminal, and the collaborative base station can be determined through more comprehensive factors, thereby improving the transmission performance and transmission quality of the base station cluster. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 A schematic diagram of a flow chart of a method for selecting a cooperative base station based on spatial correlation provided by an embodiment of the present invention;

[0032] Figure 2 A schematic diagram of an algorithm for determining a cooperative base station provided in an embodiment of the present invention;

[0033] Figure 3 A schematic diagram of a flow chart of a method for determining spectrum efficiency provided by an embodiment of the present invention;

[0034] Figure 4 A schematic diagram of the structure of a user terminal provided by an embodiment of the present invention;

[0035] Figure 5 A schematic diagram for comparing spectrum efficiencies provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0036] The present invention is further described in detail below with reference to specific embodiments, but the embodiments of the present invention are not limited thereto.

[0037] The spatial correlation-based cooperative base station selection method provided in the embodiment of the present invention can be applied to user terminals such as mobile terminals, personal notebook computers, supercomputers, etc. The embodiment of the present invention does not impose any restrictions on the specific type of user terminals.

[0038] Figure 1 The flowchart of a method for selecting a cooperative base station based on spatial correlation provided by an embodiment of the present invention is shown. As an example but not a limitation, the method 100 can be applied to the above user terminal. The method 100 can include steps S101-S102, and each step is described below.

[0039] S101, determining a correlation coefficient between a user terminal and a base station according to channel information between the user terminal and the base station.

[0040] In a possible implementation, the user terminal can determine the downlink channel between the user terminal and each base station based on the channel information between the user terminal and each base station. Then, the downlink channel is decomposed to obtain a singular value matrix. The correlation coefficient between the user terminal and the base station is determined based on the singular value matrix between the user terminal and the base station.

[0041] In an example, the user terminal k may use the Minimum Mean Square Error (MMSE) method to calculate the downlink channel h between the user terminal k and the lth base station. lk An estimate is made to obtain the downlink channel between the user terminal k and the lth base station.

[0042] Exemplarily, the downlink channel between the user terminal k and the lth base station may satisfy the following formula:

[0043]

[0044] Among them, h lk is the estimated downlink channel between user terminal k and the lth base station, is the spatial correlation matrix of the downlink channel between user terminal k and the lth base station, is the covariance matrix of the pilot-based received signal, is the received signal, η l is the square root of the downlink transmission power of the lth base station, τ p is the coherent pilot time.

[0045] Exemplarily, the channel information may include parameters such as a received signal, a square root of a downlink transmission power of the lth base station, and a coherent pilot time.

[0046] In one example, singular value decomposition can be performed on the downlink channel between the user terminal and the base station to obtain a singular value matrix. That is, h lk=UΣV H , where Σ is the singular value matrix, U is the left singular vector matrix, and V is the right singular vector matrix.

[0047] In an example, the maximum value and the minimum value may be selected from all non-zero elements of the singular value matrix, and the ratio of the maximum value to the minimum value may be determined as the correlation coefficient between the base station and the user terminal.

[0048] S102: Determine at least one cooperative base station for serving the user terminal from all base stations according to the correlation coefficient and the large-scale fading coefficient, and obtain a base station cluster of the user terminal.

[0049] In one possible implementation, see Figure 2 , the user end can determine the base station that is closer to the user end and has stronger correlation (that is, has a smaller large-scale fading coefficient and a larger correlation coefficient) as a cooperative base station through steps S1021-S1025, thereby obtaining a base station cluster.

[0050] S1021, arranging all base stations in ascending order according to the large-scale fading coefficients between the base stations and the user terminals to obtain a first first sequence.

[0051] Exemplarily, the magnitude of the large-scale fading coefficient is proportional to the distance between the base station and the user terminal.

[0052] For example, if there are 5 base stations that can provide services to user terminal k, they are recorded as base station 1, base station 2, ..., base station 5. Their large-scale fading coefficients are: 1, 2, 3, 10, 2. The first sequence obtained by sorting the base stations according to the large-scale fading coefficients is: base station 1, base station 2, base station 5, base station 3, base station 4.

[0053] S1022, determining whether a difference in large-scale fading coefficients between the second base station and the first base station in the hth first sequence is less than a large-scale fading coefficient threshold, and whether a correlation coefficient difference is greater than a spatial correlation threshold.

[0054] Exemplarily, the difference of the large-scale fading coefficients is the large-scale fading coefficient of the second base station minus the large-scale fading coefficient of the first base station.

[0055] Exemplarily, the correlation coefficient difference is the correlation coefficient of the second base station minus the correlation coefficient of the first base station.

[0056] In an example, if the difference between the large-scale fading coefficients of the two base stations is smaller than the large-scale fading coefficient threshold and the difference between the correlation coefficients is larger than the spatial correlation threshold, step S1023 may be performed.

[0057] For example, see the examples above and Figure 2 , if lsf dB (sorted_lsf(2))-lsf dB (sorted_lsf(1))<ε d , and (rat(lsf dB (2))-rat(lsf dB (1)))>ε sc , then step S1023 can be performed. Wherein, sorted_lsf(1) is the first base station in the first first sequence, that is, base station 1, sorted_lsf(2) is the second base station in the first first sequence, that is, base station 2, lsf dB (sorted_lsf(1)) is the large-scale fading coefficient of base station 1, lsf dB (sorted_lsf(2)) is the large-scale fading coefficient of base station 2, ε d is the large-scale fading coefficient threshold, rat(lsf dB (1)) is the correlation coefficient of base station 1, rat(lsf dB (2)) is the correlation coefficient of base station 2, ε sc is the spatial correlation threshold.

[0058] In another example, if the difference between the large-scale fading coefficients of the two base stations is greater than or equal to the large-scale fading coefficient threshold, or the difference between the correlation coefficients of the two base stations is less than the spatial correlation threshold, step S1024 may be performed.

[0059] S1023: determine the second base station in the hth first sequence as a cooperative base station and add it to the base station cluster, and delete the second base station in the hth first sequence to obtain an h+1th first sequence.

[0060] For example, if base station 1 and base station 2 meet the conditions, base station 2 may be determined as a cooperative base station and added to base station cluster M. The second first sequence after deleting base station 2 is: base station 1, base station 5, base station 3, base station 4.

[0061] S1024: determine the first base station in the hth first sequence as a coordinated base station and add it to the base station cluster, and delete the first base station in the hth first sequence to obtain an h+1th first sequence.

[0062] For example, when base station 1 and base station 2 do not meet the above conditions, base station 1 can be determined as a cooperative base station and added to base station cluster M. The second first sequence after deleting base station 1 is: base station 2, base station 5, base station 3, base station 4.

[0063] S1025: Determine whether h is greater than or equal to the maximum number of cooperative base stations.

[0064] In an example, when h is greater than or equal to the maximum number NUM of cooperative base stations, the process may be terminated to obtain a final base station cluster.

[0065] In another example, when h is less than the maximum number NUM of cooperative base stations, step S1022 may be performed, where h=h+1.

[0066] Optionally, method 100 may further include steps S103 and S104.

[0067] S103, evaluating the service effect of the base station cluster according to the precoding matrix between each cooperative base station and the user terminal, and determining the spectrum efficiency of the base station cluster in serving the user terminal.

[0068] Exemplarily, the precoding matrix can be the first N right singular vector matrix V r N r is the number of receiving antennas at the user end.

[0069] In some embodiments, see Figure 3 The user terminal can determine the spectrum efficiency of the base station cluster serving the user terminal through steps S1031-S1034.

[0070] S1031 , quantize the precoding matrix between the ith cooperative base station and the gth served user terminal using a standard codebook to obtain a quantized precoding matrix between the ith cooperative base station and the gth served user terminal.

[0071] Exemplarily, i and g are both positive integers greater than or equal to 1.

[0072] Exemplarily, the served user terminals include all user terminals served by the i-th cooperative base station including user terminal k.

[0073] In a possible implementation manner, the precoding matrix between the user terminal and the cooperative base station may be quantized based on the 3GPP standard Type I codebook of DFT (ie, DFT codebook) to obtain a quantized precoding matrix.

[0074] Exemplarily, the quantization precoding matrix (ie, the quantization criterion) may satisfy the following formula:

[0075]

[0076] in, is the quantized precoding matrix, H is the precoding matrix, x is a column in the standard codebook, is the standard codebook.

[0077] Exemplarily, the codebook used in quantization may be generated in advance.

[0078] In one example, the DFT codebook is an equal gain codebook generated based on the DFT matrix. It can find the optimal beamforming vector through a low-complexity exhaustive search. The DFT codebook can evenly divide the entire angle space, and because its own Vandermonde structure codewords are mutually orthogonal, the full diversity gain of the transmitter can be obtained in the MIMO system.

[0079] For example, for a uniform linear array with an element spacing of half a wavelength, the codeword vector w(l) of the DFT codebook can be expressed as:

[0080]

[0081] Where b = 0, 1 / N t ,...,(N t -1) / N t , N t The number of antennas equipped for the base station, T represents transposition.

[0082] For example, from R10 of the LTE standard to the present, 3GPP has always adopted the DFT codebook as the standard codebook and made improvements based on the DFT codebook. The Type I codebook (i.e., DFT codebook) used in the present invention follows the W=W used in the LTE codebook design. 1 W 2 The two-level codebook structure of 1 is the long-term characteristic codebook of the channel, W 2 It is the short-term subband characteristic codebook of the channel, which is a simple extension of the DFT codebook as a whole. First, based on the Kronecker product, the DFT codebook is extended from a linear array to a rectangular array. Secondly, when the number of antenna elements in the vertical or horizontal dimension is greater than 1, the oversampling factor is increased to support a certain phase rotation of the codebook as a whole. Finally, since the base station is equipped with a dual-polarization array when deployed, the W 2 The quantization of the polarization phase is fed back in.

[0083] Exemplarily, the beam set of the horizontal dimension and the beam set of the vertical dimension for generating the DFT codebook may satisfy the following formulas respectively:

[0084]

[0085]

[0086] Where q1=0,1,...,O 1 -1 and q2=0,1,...,O 2 -1 is the rotation factor for the horizontal and vertical dimensions respectively, N 1 is the number of antennas in the horizontal dimension of the array, O 1is the oversampling factor, N 2 is the number of vertical antennas, O 2 is the oversampling factor, v q1,n1 is the beam set in the horizontal dimension, u q2,n2 is the beam set in the vertical dimension.

[0087] Exemplary, including N 1 O 1 N 2 O 2 The DFT codebook of the spatial domain beam set of beams can be obtained by multiplying the two-dimensional DFT beams through the Kronecker product. The DFT codebook can satisfy the following formula:

[0088]

[0089] Wherein, D is the DFT codebook.

[0090] The user end can measure the channel information and select the broadband beam group to generate the codebook W for each layer of precoding vector from the beam set in the spatial domain according to the above quantization criteria. 1 .W 1 It is a block diagonal matrix. Each diagonal block B represents a beam group selected in a polarization direction. Antenna arrays in different polarization directions use the same beam group. The beam group contains L beams. L can be configured as 1 or 4. When L=4, several adjacent beams of the strongest beam are selected to form a beam group. The short-term inherent characteristic codebook structure of the DFT codebook is Where P is used to select a beam from the broadband beam group when L = 4, and PSK uniform quantization is used to quantize the phase difference between two polarization directions.

[0091] S1032: Determine a global quantization precoding matrix of the ith cooperative base station according to the quantization precoding matrix between the ith cooperative base station and the gth served user terminal.

[0092] Exemplarily, the quantization precoding matrix between the ith cooperative base station and the service user terminal of the ith cooperative base station may be combined to obtain the global quantization precoding matrix of the ith cooperative base station.

[0093] Exemplarily, the global quantization precoding matrix of the i-th cooperative base station may satisfy the following formula:

[0094]

[0095] Among them, V i is the global quantization precoding matrix of the ith cooperative base station, The quantization precoding matrix of the hth user terminal served by the i-th cooperative base station, N serviceis the total number of service users of the ith cooperative base station.

[0096] S1033 , performing a precoding operation on the global quantization precoding matrix of the i th cooperative base station to obtain the global precoding matrix of the i th cooperative base station.

[0097] In an example, distributed ZF precoding may be used to perform a precoding operation on the global quantization precoding matrix of the i-th cooperative base station.

[0098] Exemplarily, the global precoding matrix of the i-th cooperative base station may satisfy the following formula:

[0099]

[0100] Among them, W i is the global precoding matrix of the ith cooperative base station, is the power allocation matrix, satisfying P ig is the transmission power allocated by the i-th cooperative base station to the g-th service user terminal, Representation Matrix The (g-1,g)Nth r List.

[0101] Exemplarily, since the FDD system cannot directly obtain channel information, the present invention adopts an average power control strategy, that is, the transmission power allocated by the i-th base station to the g-th service user terminal is P ig =P i / N service , where P i is the total power of the i-th cooperative base station.

[0102] S1034, determining the spectrum efficiency of the base station cluster serving the user terminal according to the downlink channel between the user terminal and each coordinated base station respectively, and the global quantization precoding matrix of all coordinated base stations.

[0103] Exemplarily, the spectrum efficiency of a base station cluster serving a user terminal k may satisfy the following formula:

[0104]

[0105] Among them, R k is the spectrum efficiency of base station cluster M serving user terminal k, σ n 2 is the noise, w ig is the g-th column of the global quantization precoding matrix of the i-th cooperative base station.

[0106] S104: Adjust the coordinated base stations in the base station cluster according to the spectrum efficiency.

[0107] Exemplarily, the service effect of the base station cluster can be measured by spectrum efficiency. When the service effect is not good, a new base station can be selected to be replaced or added to the base station cluster M to improve the service effect of the base station cluster M.

[0108] According to the method provided by the present invention, the cooperative base station used to serve the user terminal is jointly determined by the large-scale fading coefficient and the correlation coefficient between the base station and the user terminal, and the cooperative base station can be determined by more comprehensive factors, thereby improving the transmission performance and transmission quality of the base station cluster. Furthermore, the cooperative base stations in the base station cluster are adjusted according to the spectrum efficiency of the base station cluster serving the user terminal, which can further improve the transmission performance and transmission quality of the base station cluster.

[0109] Figure 4 The diagram is a schematic diagram of the structure of a user terminal provided by an embodiment of the present invention. As an example but not a limitation, the user terminal 400 may include a processing unit 410 .

[0110] The processing unit 410 may be used to:

[0111] Determine a correlation coefficient between the user terminal and each base station according to channel information between the user terminal and the base station;

[0112] At least one cooperative base station for serving the user terminal is determined from all base stations according to the correlation coefficient and the large-scale fading coefficient, so as to obtain a base station cluster of the user terminal.

[0113] In a possible implementation, the processing unit 410 can be specifically used to determine the downlink channel between the user terminal and each base station based on the channel information; decompose the downlink channel to obtain a singular value matrix; and determine the ratio of the maximum value to the minimum value in the singular value matrix as the correlation coefficient.

[0114] In a possible implementation, the processing unit 410 can be specifically used to arrange all base stations in ascending order according to the large-scale fading coefficient between the base station and the user terminal to obtain the first first sequence; determine whether the difference in large-scale fading coefficient between the second base station and the first base station in the h-th first sequence is less than the large-scale fading coefficient threshold, and whether the correlation coefficient difference is greater than the spatial correlation threshold; if the difference in large-scale fading coefficient between the second base station and the first base station in the h-th first sequence is less than the large-scale fading coefficient threshold, and the correlation coefficient difference is greater than the spatial correlation threshold, then the second base station in the h-th first sequence is determined as a collaborative base station and added to the base station cluster, and the second base station in the h-th first sequence is deleted to obtain the h+1-th first sequence; otherwise, the first base station in the h-th first sequence is determined as a collaborative base station and added to the base station cluster, and the first base station in the h-th first sequence is deleted to obtain the h+1-th first sequence.

[0115] Exemplarily, the magnitude of the large-scale fading coefficient is proportional to the distance between the base station and the user terminal.

[0116] Exemplarily, h=1, 2...NUM, where NUM is the maximum number of cooperative base stations in the base station cluster.

[0117] In a possible implementation, the processing unit 410 also obtains a precoding matrix when decomposing the downlink channel. The processing unit 410 can also be used to evaluate the service effect of the base station cluster according to the precoding matrix between each cooperative base station and the user terminal, determine the spectrum efficiency of the base station cluster serving the user terminal, and adjust the cooperative base stations in the base station cluster according to the spectrum efficiency.

[0118] In a possible implementation, the processing unit 410 can also be specifically used to quantize the precoding matrix between the ith collaborative base station and the gth service user terminal through a standard code book to obtain a quantized precoding matrix between the ith collaborative base station and the gth service user terminal, wherein i and g are positive integers greater than or 1, the service user terminal is the user terminal served by the ith collaborative base station, and the service user terminal includes the user terminal; according to the quantized precoding matrix between the ith collaborative base station and the gth service user terminal, determine the global quantized precoding matrix of the ith collaborative base station; perform a precoding operation on the global quantized precoding matrix of the ith collaborative base station to obtain the global precoding matrix of the ith collaborative base station; and determine the spectrum efficiency of the base station cluster serving the user terminal according to the downlink channel between the user terminal and each collaborative base station, and the global quantized precoding matrix of all collaborative base stations.

[0119] Exemplarily, i and g are both positive integers greater than or equal to 1.

[0120] Exemplarily, the served user terminal is a user terminal served by the i-th cooperative base station, and the served user terminal includes the above-mentioned user terminal.

[0121] In order to better illustrate the beneficial effects of the present invention, the following simulation experiments were conducted:

[0122] Exemplarily, the software platform for the simulation experiment is: MATLAB R2023b.

[0123] For example, the simulated delay is randomly distributed in a circle with a radius of 300 meters. 30 base stations and 1 user end are randomly distributed in a circle with a radius of 300 meters. Each base station is equipped with 8 antennas. The array is a rectangular array with 4 elements in the horizontal direction and 2 elements in the vertical direction. The user end is equipped with a uniform linear array with 2 antennas. The vertical and horizontal elements of all arrays are evenly spaced by half a wavelength. The channel adopts the calculation formula of LOS probability and large-scale fading in the 3GPP standard UMi scenario. Small-scale fading adopts SV channel, and its expression is

[0124]

[0125] Among them, N ray is the multipath number, α a is the gain of the ath path, and represents the antenna response of the transmitting and receiving ends, where and are the azimuth and elevation of arrival and departure respectively.

[0126] The antenna response vector can be expressed as

[0127]

[0128] Among them, N h and N h are the number of elements in the horizontal and vertical dimensions of the antenna array, respectively, and N = N h N v .

[0129] Taking the azimuth angle φ as an example, it can be written as of the form, where is the angle calculated based on the base station and user positions and the array direction, called the direct path angle. Δφ is the perturbation value of the azimuth angle, which obeys The Gaussian distribution of , σ is the angle spread of the azimuth angle φ. During simulation, the angle spread of each base station to the user channel is of uniform distribution.

[0130] In the Umi scenario, the large-scale fading coefficient threshold ε d Set to 20, the spatial correlation coefficient threshold ε sc Set to 40.

[0131] Figure 5 A schematic diagram showing comparison of spectrum efficiency provided by an embodiment of the present invention is shown.

[0132] See also Figure 5 Under the above simulation conditions, the cooperative base stations are determined by the method provided by the present invention, the random selection method and the current method of selecting only by large-scale fading coefficients, and the spectrum efficiency change curves obtained by each method are determined by the process shown in step S103 of method 100. Figure 5 , wherein 501 is a curve diagram showing the variation of the spectrum efficiency obtained by the method provided by the present invention, 502 is a curve diagram showing the variation of the spectrum efficiency obtained by a random selection method, and 503 is a curve diagram showing the variation of the spectrum efficiency obtained by the current method of selecting only a large-scale fading coefficient.

[0133] The following table 1 shows the average rate and terminal rate of information transmission obtained by different methods.

[0134] Table 1

[0135] Average rate (bits / Hz / s) Interrupt rate (bits / Hz / s) Random Selection 10.243 6.544 Large scale fading coefficient 12.621 8.076 The present invention 13.307 9.264

[0136] Exemplarily, the outage rate is defined as the minimum rate among the top 95% of rates.

[0137] See also Figure 5 From Table 1, it can be seen that, under the same conditions, the method provided by the present invention has the highest spectrum efficiency, which is about 5% better in spectrum efficiency and 10% better in interruption rate than the current method of selecting cooperative base stations only through large-scale coefficients.

[0138] According to the method provided by the present invention, the cooperative base station used to serve the user terminal is jointly determined by the large-scale fading coefficient and the correlation coefficient between the base station and the user terminal. The cooperative base station can be determined through more comprehensive factors, thereby improving the transmission performance and transmission quality of the base station cluster.

[0139] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0140] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

Claims

1. A method for selecting a cooperative base station based on spatial correlation, characterized in that: The method is applied to a user terminal, and the method comprises: Determining a correlation coefficient between the user terminal and each base station according to channel information between the user terminal and the base station; comprising: Determining a downlink channel between the user terminal and each base station according to the channel information; Decomposing the downlink channel to obtain a singular value matrix; determining the ratio of the maximum value to the minimum value in the singular value matrix as the correlation coefficient; The downlink channel is decomposed to obtain a precoding matrix; the service effect of the base station cluster is evaluated according to the precoding matrix between each of the cooperative base stations and the user terminal, and the spectrum efficiency of the base station cluster serving the user terminal is determined; and the cooperative base stations in the base station cluster are adjusted according to the spectrum efficiency; Determining at least one cooperative base station for serving the user terminal from all base stations according to the correlation coefficient and the large-scale fading coefficient, and obtaining a base station cluster of the user terminal; comprising: Arranging all base stations in ascending order according to the large-scale fading coefficient between the base station and the user terminal to obtain a first first sequence, wherein the magnitude of the large-scale fading coefficient is proportional to the distance between the base station and the user terminal, h =1,2...NUM, NUM is the maximum number of the cooperative base stations in the base station cluster; Determine in h whether the difference in large-scale fading coefficients between the second base station and the first base station in the first sequence is less than a large-scale fading coefficient threshold, and whether the difference in correlation coefficients is greater than a spatial correlation threshold; If in the h If the difference in large-scale fading coefficient between the second base station and the first base station in the first sequence is less than the large-scale fading coefficient threshold, and the difference in correlation coefficient is greater than the spatial correlation threshold, then the first base station h The second base station in the first sequence is determined as the cooperative base station and added to the base station cluster, and the first base station is deleted. h The second base station in the first sequence gets the h +1 first sequence; Otherwise, the h The first base station in the first sequence is determined as the cooperative base station and added to the base station cluster, and the first base station in the first sequence is deleted. h The first base station in the first sequence obtains the first h +1 first sequence.

2. The method according to claim 1, characterized in that The evaluating the service effect of the base station cluster according to the precoding matrix between each of the cooperative base stations and the user terminal to determine the spectrum efficiency of the base station cluster serving the user terminal includes: Through the standard code book i The cooperative base station g The precoding matrix between the serving user terminals is quantized to obtain the first i a cooperative base station and the g The quantization precoding matrix between the service user terminals, where i and g are all positive integers greater than or equal to 1, and the service user terminal is the first i A user terminal served by a cooperative base station, wherein the served user terminal includes the user terminal; According to the said i a cooperative base station and the g The quantization precoding matrix between the serving user terminals is determined as follows: i The global quantized precoding matrix of the coordinated base stations; Regarding the i The global quantization precoding matrix of the cooperative base station is used to perform precoding operation, and the first i The global precoding matrix of the coordinated base stations; The spectrum efficiency of the base station cluster serving the user terminal is determined according to the downlink channels between the user terminal and each of the coordinated base stations, and the global quantization precoding matrix of all the coordinated base stations.

3. A user terminal, characterized in that: The user terminal includes a processing unit, and the processing unit is used to: Determining a correlation coefficient between the user terminal and each base station according to channel information between the user terminal and the base station; comprising: Determining a downlink channel between the user terminal and each base station according to the channel information; Decomposing the downlink channel to obtain a singular value matrix; determining the ratio of the maximum value to the minimum value in the singular value matrix as the correlation coefficient; Decomposing the downlink channel, and obtaining a precoding matrix; evaluating the service effect of the base station cluster according to the precoding matrix between each cooperative base station and the user terminal, and determining the spectrum efficiency of the base station cluster serving the user terminal; adjusting the cooperative base stations in the base station cluster according to the spectrum efficiency; Determining at least one cooperative base station for serving the user terminal from all base stations according to the correlation coefficient and the large-scale fading coefficient, and obtaining a base station cluster of the user terminal; comprising: Arranging all base stations in ascending order according to the large-scale fading coefficient between the base station and the user terminal to obtain a first first sequence, wherein the magnitude of the large-scale fading coefficient is proportional to the distance between the base station and the user terminal, h =1,2...NUM, NUM is the maximum number of the cooperative base stations in the base station cluster; Determine in h whether the difference in large-scale fading coefficients between the second base station and the first base station in the first sequence is less than a large-scale fading coefficient threshold, and whether the difference in correlation coefficients is greater than a spatial correlation threshold; If in the h If the difference in large-scale fading coefficient between the second base station and the first base station in the first sequence is less than the large-scale fading coefficient threshold, and the difference in correlation coefficient is greater than the spatial correlation threshold, then the first base station h The second base station in the first sequence is determined as the cooperative base station and added to the base station cluster, and the first base station is deleted. h The second base station in the first sequence gets the h +1 first sequence; Otherwise, the h The first base station in the first sequence is determined as the cooperative base station and added to the base station cluster, and the first base station in the first sequence is deleted. h The first base station in the first sequence obtains the first h +1 first sequence.

4. The user terminal according to claim 3, characterized in that: The processing unit is further specifically used for: Through the standard code book i The cooperative base station g The precoding matrix between the serving user terminals is quantized to obtain the first i a cooperative base station and the g The quantization precoding matrix between the service user terminals, where i and g are all positive integers greater than or equal to 1, and the service user terminal is the first i A user terminal served by a cooperative base station, wherein the served user terminal includes the user terminal; According to the said i a cooperative base station and the g The quantization precoding matrix between the serving user terminals is determined as follows: i The global quantized precoding matrix of the coordinated base stations; Regarding the i The global quantization precoding matrix of the cooperative base station is used to perform precoding operation, and the first i The global precoding matrix of the coordinated base stations; The spectrum efficiency of the base station cluster serving the user terminal is determined according to the downlink channels between the user terminal and each of the coordinated base stations, and the global quantization precoding matrix of all the coordinated base stations.

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