Multi-user interference suppression method and device, equipment and storage medium

Abstract

The invention provides a multi-user interference suppression method and device, equipment and a storage medium, and relates to the technical field of communication. The method comprises the following steps: acquiring a feedback equivalent channel matrix of interference of a first antenna unit on a terminal; carrying out singular value decomposition on the feedback equivalent channel matrix, and carrying out carrier dimension smoothing processing on a singular value right matrix obtained through decomposition to obtain a pre-coding matrix; performing polynomial compression on the precoding matrix to obtain a feedback result; and sending the feedback result to the second antenna unit. According to the scheme of the invention, the method can achieve the reporting of interference, prevents the information transmitted by the first antenna unit from interfering with the terminal associated with the second antenna unit, can achieve the efficient cooperation of a plurality of distributed antennas, and improves the performance of precoding or beamforming.

Description

Technical Field

[0001] This application relates to the field of communication technology, specifically to a method, apparatus, device, and storage medium for suppressing interference among multiple users. Background Technology

[0002] With the full commercialization of 5G and the gradual development of 6G research, the demands for spectrum efficiency, coverage, and reliability in wireless communication systems are constantly increasing. Distributed multiple-in multiple-out (D-MIMO), as a key technology for next-generation wireless communication, significantly improves system performance by distributing antenna elements across multiple geographical locations, becoming one of the important technical means to enhance indoor coverage and increase the capacity of urban hotspots.

[0003] D-MIMO transmits data collaboratively through geographically dispersed antenna elements. In particular, precoding techniques based on zero-forcing or MU zero vectors, or beamforming techniques, can theoretically significantly improve system capacity and coverage. However, in actual product deployment, the core challenge lies in achieving efficient collaboration among multiple distributed antennas, especially antenna consistency calibration and time synchronization. These issues directly affect the performance of precoding or beamforming, making it difficult to achieve the throughput gain provided by D-MIMO. Summary of the Invention

[0004] The purpose of this application is to provide a multi-user interference suppression method, apparatus, device, and storage medium to achieve efficient cooperation of multiple distributed antennas and improve the performance of precoding or beamforming.

[0005] To achieve the above objectives, embodiments of this application provide a multi-user interference suppression method, comprising:

[0006] Obtain the feedback equivalent channel matrix of the interference of the first antenna element to the terminal;

[0007] The feedback equivalent channel matrix is ​​subjected to singular value decomposition, and the carrier dimension of the right singular value matrix obtained by decomposition is smoothed to obtain the precoding matrix.

[0008] The precoding matrix is ​​subjected to polynomial compression to obtain the feedback result;

[0009] The feedback result is sent to the second line unit.

[0010] Optionally, obtaining the feedback equivalent channel matrix of the interference of the first antenna element to the terminal includes:

[0011] Based on the first signal received from the first antenna element, obtain the first channel matrix between the first antenna element and the terminal;

[0012] Based on the second signal received from the second antenna unit, obtain the second channel matrix between the second antenna unit and the terminal;

[0013] Based on the first channel matrix and the second channel matrix, obtain the feedback equivalent channel matrix of the interference of the first antenna element to the terminal.

[0014] Optionally, obtaining the feedback equivalent channel matrix of the interference of the first antenna element to the terminal based on the first channel matrix and the second channel matrix includes:

[0015] Perform singular value decomposition on the second channel matrix to obtain the left singular value matrix;

[0016] Based on the singular value left matrix and the first channel matrix, the feedback equivalent channel matrix of the interference of the first antenna element to the terminal is obtained.

[0017] Optionally, the method further includes:

[0018] The terminal receives first information sent by the second antenna unit, the first information being used to indicate an antenna port group associated with the terminal, the antenna port group corresponding to the second antenna unit.

[0019] Optionally, the step of performing polynomial compression on the precoding matrix and obtaining the feedback result includes:

[0020] The feedback result is obtained based on the precoding matrix and the length of the subcarrier block.

[0021] Optionally, obtaining the feedback result based on the precoding matrix and the length of the subcarrier-blocked block includes:

[0022] The first matrix is ​​obtained based on the length of the subcarrier-divided block and the degree of the polynomial.

[0023] Based on the first matrix and the pre-encoding matrix, obtain the fitting parameters;

[0024] The fitted parameters are determined as the feedback result.

[0025] Optionally, the number of columns in the first matrix is ​​determined based on the degree of the polynomial, and the number of rows in the first matrix is ​​determined based on the length of the subcarrier block.

[0026] This application also provides a multi-user interference suppression method, including:

[0027] The receiving terminal sends a feedback result, which is obtained by the terminal performing polynomial compression on the precoding matrix. The precoding matrix is ​​obtained by performing singular value decomposition on the feedback equivalent channel matrix of the interference of the terminal by the first antenna element, and then performing carrier dimension smoothing on the right singular value matrix obtained by the decomposition.

[0028] Based on the feedback result, communication is established with the first antenna unit, enabling the first antenna unit to transmit downlink information based on the precoding matrix obtained through the feedback result.

[0029] This application also provides a multi-user interference suppression method apparatus, including:

[0030] The first acquisition module is used to acquire the feedback equivalent channel matrix of the interference of the first antenna element to the terminal;

[0031] The second acquisition module is used to perform singular value decomposition on the feedback equivalent channel matrix and smooth the right singular vector matrix obtained by decomposition in the carrier dimension to obtain a precoding matrix.

[0032] The third acquisition module is used to perform polynomial compression on the precoding matrix and obtain feedback results;

[0033] The first sending module is used to send the feedback result to the network device.

[0034] This application also provides a multi-user interference suppression method apparatus, including:

[0035] The first receiving module is used to receive feedback results sent by the terminal. The feedback results are obtained based on the terminal performing polynomial compression on the precoding matrix. The precoding matrix is ​​obtained based on the first antenna element performing singular value decomposition on the feedback equivalent channel matrix of the interference of the terminal. The carrier dimension is smoothed on the right singular value matrix obtained by decomposition.

[0036] The second transmitting module is used to communicate with the first antenna unit based on the feedback result, so that the first antenna unit transmits downlink information based on the precoding matrix obtained through the feedback result.

[0037] This application also provides a multi-user interference suppression method apparatus, including: a transceiver, a processor, a memory, and a program or instructions stored in the memory and executable on the processor; when the processor executes the program or instructions, it implements the above-described multi-user interference suppression method.

[0038] This application also provides a readable storage medium storing a program or instructions thereon, which, when executed by a processor, implements the steps in the multi-user interference suppression method described above.

[0039] The beneficial effects of the above technical solution in this application are as follows:

[0040] The method in this embodiment obtains the feedback equivalent channel matrix of interference from the first antenna unit to the terminal, performs singular value decomposition on the feedback equivalent channel matrix, smooths the carrier dimension of the obtained singular value matrix to obtain a precoding matrix, performs polynomial compression on the precoding matrix, obtains the feedback result, and sends the feedback result to the second antenna unit so that the second antenna unit can communicate with the first antenna unit. The first antenna unit then transmits downlink data based on the precoding matrix determined by the feedback result. In this way, interference reporting can be achieved, avoiding interference from the information transmitted by the first antenna unit to the terminal associated with the second antenna unit. This enables efficient cooperation of multiple distributed antennas and improves the performance of precoding or beamforming. Attached Figure Description

[0041] Figure 1 This is one of the flowcharts illustrating the multi-user interference suppression method according to an embodiment of this application;

[0042] Figure 2 This is a schematic diagram of a MU-MIMO system model for flower arrangement networking;

[0043] Figure 3 A schematic diagram comparing the amplitudes of the real part of the matrix without singular value right-matrix smoothing across all subcarriers with those of the matrix with singular value right-matrix smoothing across all subcarriers;

[0044] Figure 4 This is a schematic diagram comparing the real part of the equivalent channel without smoothing with the real part of the equivalent channel with smoothing.

[0045] Figure 5 A schematic diagram showing the precoded values ​​on adjacent subcarriers of the same OFDM symbol;

[0046] Figure 6 A schematic diagram of the subcarrier envelopes for the real and imaginary parts of a channel within a block;

[0047] Figure 7 A schematic diagram of the fitting process to compress one element;

[0048] Figure 8 This is a schematic diagram comparing the original uncompressed SINR with the SINR obtained by polynomial fitting compression.

[0049] Figure 9 This is a second schematic flowchart of the multi-user interference suppression method according to an embodiment of this application;

[0050] Figure 10This is one of the module schematic diagrams of a multi-user interference suppression device according to an embodiment of this application;

[0051] Figure 11 This is one of the structural schematic diagrams of a multi-user interference suppression device according to an embodiment of this application;

[0052] Figure 12 This is a second schematic diagram of the multi-user interference suppression device according to an embodiment of this application;

[0053] Figure 13 This is a second schematic diagram of the structure of a multi-user interference suppression device according to an embodiment of this application. Detailed Implementation

[0054] To make the technical problems, technical solutions and advantages of this application clearer, a detailed description will be provided below in conjunction with the accompanying drawings and specific embodiments.

[0055] It should be understood that the phrase "one embodiment" or "an embodiment" throughout the specification means that a specific feature, structure, or characteristic related to the embodiment is included in at least one embodiment of this application. Therefore, "in one embodiment" or "in an embodiment" appearing throughout the specification does not necessarily refer to the same embodiment. Furthermore, these specific features, structures, or characteristics can be combined in any suitable manner in one or more embodiments.

[0056] In the various embodiments of this application, it should be understood that the sequence number of each process described below does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0057] In addition, the terms "system" and "network" are often used interchangeably in this article.

[0058] In the embodiments provided in this application, it should be understood that "B corresponding to A" means that B is associated with A, and B can be determined based on A. However, it should also be understood that determining B based on A does not mean that B is determined solely based on A; B can also be determined based on A and / or other information.

[0059] The following is a brief description of the technologies related to this application.

[0060] In D-MIMO and wireless network deployments, there are similar "interspersed networking" and "clustered continuous networking".

[0061] Antenna units (such as remote radio units (RRUs) or access points (APs)) are distributed non-uniformly and interspersed within the coverage area. The coverage areas of each antenna unit partially overlap but are not continuous. If different antenna units serve different users, mutual interference will occur between users in the overlapping area.

[0062] The antenna elements are divided into multiple continuous coverage clusters. The antenna elements within a cluster are extended to form a continuous coverage area through a hub. Users in the continuous coverage area do not experience interference, while users in the overlapping areas between clusters usually experience interference or cannot obtain the expected gain, such as beamforming or precoding.

[0063] To achieve the combination of D-MIMO and precoding or beamforming technologies, antenna conformance calibration and time synchronization are required. On the one hand, the hardware configuration requirements are relatively high to meet the corresponding synchronization and calibration requirements. On the other hand, even if the technical requirements are met, there are many uncertainties and impracticalities in terms of productization and actual deployment of calibration and synchronization, or the hardware cost to achieve the required results is too high.

[0064] This application mainly utilizes the uplink feedback assistance of the terminal to achieve an interference cancellation scheme between users in the downlink overlapping area of ​​different antenna elements, or between users in the overlapping area and the central user of another antenna element.

[0065] like Figure 1 As shown, an embodiment of this application provides a multi-user interference suppression method applied to a terminal, comprising:

[0066] Step 101: Obtain the feedback equivalent channel matrix of the interference of the first antenna element to the terminal;

[0067] Step 102: Perform singular value decomposition on the feedback equivalent channel matrix, and smooth the right singular value matrix obtained by decomposition according to the carrier dimension to obtain the precoding matrix.

[0068] Step 103: Perform polynomial compression on the precoding matrix and obtain the feedback result;

[0069] Step 104: Send the feedback result to the second line unit.

[0070] It should be noted that, in this embodiment, the feedback equivalent channel matrix of the interference from the first antenna unit to the terminal is obtained, the feedback equivalent channel matrix is ​​decomposed into singular values, the carrier dimension of the decomposed singular value matrix is ​​smoothed to obtain a precoding matrix, the precoding matrix is ​​compressed by polynomial, the feedback result is obtained, and the feedback result is sent to the second antenna unit so that the second antenna unit communicates with the first antenna unit. The first antenna unit transmits downlink data according to the precoding matrix determined by the feedback result. In this way, interference reporting can be realized, the information transmitted by the first antenna unit can be prevented from interfering with the terminal associated with the second antenna unit, and efficient cooperation of multiple distributed antennas can be realized, improving the performance of precoding or beamforming.

[0071] It should be noted that the second antenna unit is an antenna unit serving the terminal, while the first antenna unit is an antenna unit that causes interference to the terminal; the antenna unit mentioned in the embodiments of this application can be an RRU, AP, etc.

[0072] It should also be noted that, in this embodiment, smoothing the right singular value matrix obtained from the decomposition along the carrier dimension reduces the difficulty of compressed feedback, improves the feedback data compression ratio, and reduces the feedback bandwidth requirement. Since the smoothing is applied to the feedback precoding matrix, the equivalent channel formed after the interaction between the precoding matrix and the actual channel also becomes smooth, resulting in significant gains in channel estimation, noise estimation, and equalization performance.

[0073] It should be noted that the smoothing process in the carrier dimension in this application can be understood as the smoothing process in the subcarrier dimension.

[0074] This embodiment of the application achieves simultaneous downlink multi-user service by calculating and feeding back the precoding matrix, reducing latency, significantly reducing interference between different users, and improving system throughput. The first antenna unit uses the precoding matrix obtained from the feedback result to perform weighted transmission of downlink data, thus the interference of the first antenna unit to unrelated terminals is very small, almost zero, achieving the purpose of interference suppression.

[0075] The model and principles corresponding to this application will be explained below.

[0076] Taking RRUs as the antenna unit as an example, assuming each RRU is configured with 4 antennas and each terminal is also configured with 4 antennas. For interleaved scenarios, the main focus is on the cooperation between adjacent RRUs. The technical solution in this application mainly uses 2 RRUs as the basic system solution for introduction.

[0077] To illustrate the following technical solution, a 5G system can be used as an example (of course, this application can be used for other wireless systems or future 6G systems). The number of Channel State Information Reference Signal (CSI-RS) ports and packet configuration are broadcast through the Synchronization Signal Block (SSB) channel of the 5G system. UE1 and UE2 are assumed to be able to estimate the channel between the RRU and UE respectively through the downlink common CSI-RS. Figure 2 For example, the current number of downlink ports or antennas in the CSI-RS can be configured to be 8, with the first 4 ports configured as Group 1 ports, transmitting pilot signals through RRU1, and the last 4 ports configured as Group 2 ports, transmitting pilot signals through RRU2. Before cooperative interference suppression, the current user (i.e., the terminal) is informed whether it is associated with Group 1 or Group 2 via UE-specific signaling. The two terminals can measure and estimate the channel between the terminal and RRU2 and RRU1 through the 8 ports on the CSI-RS.

[0078] The system model structure adopted in this application is as follows: Figure 2 As shown.

[0079] This application applies to MU-MIMO scenario models in interleaved D-MIMO networking, or scenario models of overlapping areas between different clusters in clustered continuous networking. The RRU can determine the association between the terminal and the RRU or the Port group based on uplink data channel measurements reported by the terminal or based on the uplink Sounding Reference Signal (SRS).

[0080] Figure 2 Assuming that the Medium Access Control (MAC) determines that UE1 is associated with RRU1 and UE2 is associated with RRU2 based on SRS or other uplink channel pilots or measurement reports, and that UE1 and UE2 are both in the overlapping area or one of them is in the overlapping area and the other is not, the MAC layer also needs to perform user pairing MU-MIMO on the scheduling side based on uplink SRS measurements or uplink data channel pilot measurements.

[0081] UE1 estimates the channel matrix by receiving the pilot signals transmitted by RRU1. The channel matrix is ​​estimated by receiving the pilot signals transmitted by RRU2. .

[0082] UE2 estimates the channel matrix by receiving the pilot signals transmitted by RRU2. The channel matrix is ​​estimated by receiving the pilot signals transmitted by RRU1. .

[0083] It should be noted that steps S101-S104 above need to be performed for both UE1 and UE2.

[0084] The principle behind this application is as follows:

[0085] Assuming that, when using precoding technology, each UE transmits two streams in the downlink direction (single-stream case is similar, or one single-stream and one dual-stream case are the same; one stream represents a 1D matrix, and two streams represent a 2D matrix), in this application, each UE receives two streams Nr=2; the precoding matrix used by RRU1 to transmit signals to UE1 is W. 11 (4x2 matrix), the precoding matrix of RRU2 for UE2 is W. 22 (4x2 matrix).

[0086] UE1 received a useful signal from RRU1: H 11 It is a 4x4 matrix.

[0087] UE1 received an interference signal from RRU2: n represents noise, H 12 It is a 4x4 matrix.

[0088] The total received signal for UE1 is: .

[0089] UE2 received an interference signal from RRU1: , For noise, H 21 It is a 4x4 matrix.

[0090] UE2 received a useful signal from RRU2: H 22 It is a 4x4 matrix.

[0091] The total received signal for UE2 is: .

[0092] After UE1 and UE2 receive y1 and y2, the minimum mean square error (MMSE) equalization is performed (taking UE1 as an example):

[0093] .

[0094] Where σ is the power of the noise, and I is the identity matrix.

[0095] For H 11 Singular Value Decomposition (SVD) is performed to obtain The equilibrium equation can be rewritten as:

[0096] .

[0097] Ignoring noise for now, extract it separately from the above formula. , unfold to get , Useful signal This is an interference signal. If... The value is zero, meaning that the interference of RRU2 to UE1 is 0.

[0098] Define the equivalent interference channel matrix If W 22 lie in Singular value right matrix In the resulting null space, it can be guaranteed that the interference to UE1 when RRU2 sends data to UE2 is zero. Similarly, for RRU1, Select W 11 exist Singular value right matrix In the resulting null space, it can be determined that the interference to UE2 when RRU1 sends data to UE1 is 0.

[0099] This application is based on the principles described above.

[0100] Optionally, in one implementation, the specific implementation of obtaining the feedback equivalent channel matrix of the interference of the first antenna element to the terminal includes:

[0101] Step 11: Obtain the first channel matrix between the first antenna element and the terminal based on the first signal received from the first antenna element;

[0102] Optionally, the first signal mentioned in the embodiments of this application may be CSI-RS.

[0103] Step 12: Obtain the second channel matrix between the second antenna unit and the terminal based on the second signal received from the second antenna unit;

[0104] Optionally, the second signal mentioned in the embodiments of this application may be CSI-RS.

[0105] Step 13: Based on the first channel matrix and the second channel matrix, obtain the feedback equivalent channel matrix of the interference of the first antenna element to the terminal;

[0106] Optionally, the specific implementation of obtaining the feedback equivalent channel matrix of the interference of the first antenna element to the terminal based on the first channel matrix and the second channel matrix includes:

[0107] Perform singular value decomposition on the second channel matrix to obtain the left singular value matrix;

[0108] Based on the singular value left matrix and the first channel matrix, the feedback equivalent channel matrix of the interference of the first antenna element to the terminal is obtained.

[0109] For example, with Figure 2 For example, the specific process by which UE2 obtains the feedback equivalent channel matrix of the interference from RRU1 to UE2 is as follows:

[0110] The channel matrix H between RRU1 and UE2 is estimated by UE2 using Group 1 of RRU1's CSI-RS. 21 That is, the first channel matrix;

[0111] The channel H between RRU2 and UE2 is estimated by UE2 through group 2 of RRU2's CSI-RS. 22 That is, the second channel matrix;

[0112] UE2 to H 22 Perform SVD decomposition: , where is U 22 That is, the singular value left matrix.

[0113] UE2 obtains the feedback equivalent channel matrix of the interference from RRU1 to UE2 (i.e., the feedback equivalent channel matrix of the interference from the first antenna element to the terminal): ;

[0114] in, The feedback equivalent channel matrix for the interference of RRU1 to UE2; This represents the number of spatial streams in UE2. Indicates taking The first row, the Nth row s2 Elements of all columns in a row. Select The left singularity matrix corresponding to the largest singularity is obtained, thus yielding the diversity gain from the multiple receiving antennas of UE2. The total number of spatial transport streams for UE2 and UE1 is... , N RRU This refers to the number of antennas or ports on an RRU, for example, N. RRU =4. Only by satisfying such a degree of freedom constraint can we guarantee that the transmission of the UE associated with this RRU will have zero interference to the adjacent RRU.

[0115] Optionally, the method further includes:

[0116] The terminal receives first information sent by the second antenna unit, the first information being used to indicate an antenna port group associated with the terminal, the antenna port group corresponding to the second antenna unit.

[0117] It should be noted that in this case, the terminal can be associated with the second antenna unit by sending the first message. Optionally, the first message can be sent via terminal-specific signaling.

[0118] Optionally, with Figure 2 For example, UE2 performs singular value decomposition on the feedback equivalent channel matrix, and performs carrier-dimension smoothing on the right-hand singular value matrix obtained by the decomposition to obtain the precoding matrix. The implementation process is as follows:

[0119] right Perform SDV decomposition: .

[0120] right Smoothing is performed on the singular value right matrix (i.e., the matrix itself). There are various smoothing techniques; one relatively simple implementation method is chosen. , Let j be the right singular value matrix after smoothing, and j be the imaginary unit in the complex matrix. To obtain The element in the last row of the text, The zero vector in, that is As the precoding matrix weights of UE1 associated with RRU1, Indicates taking The elements in the 3rd and 4th columns of all rows, W 11 This is the precoding matrix obtained by smoothing the right singular value matrix obtained from the decomposition along the carrier dimension. Other smoothing methods can also be used, but this method is simple and requires less computational power.

[0121] It should be noted that, under normal circumstances Feedback is not sent for every subcarrier; this is how it is transmitted. The required bandwidth is too large, so... Feedback is typically delivered using compressed feedback. There are various types of compression feedback. For example, in 5G, one or more resource blocks (RBs) may feed back a codebook matrix of the original encoding. However, since the feedback based on the codebook is constant modulus, it brings relatively small performance gains to actual products.

[0122] Regarding the references in this application It is not a constant modulus precoding matrix, which offers a significant performance gain compared to constant modulus. For different subcarriers... Adjacent complex elements in a number may have discontinuous phases, for example... Figure 3 The blue line in the middle is The line connecting the magnitudes of the real part of an element (1,1) across all subcarriers will form a spike between subcarriers with phase abrupt changes. Figure 3 There are multiple peaks (only 3 are marked). After smoothing (red line), the phase is smoother with almost no abrupt peaks.

[0123] Phase discontinuity has two adverse effects:

[0124] feedback The compression ratio is not high, or high compression is performed, but the accuracy loss caused by discontinuities is significant. Consequently, due to the inaccuracy of the precoding matrix, it has a significant impact on the performance loss of beamforming and precoding.

[0125] because The discontinuity of the matrix, proceed Precoded and actual channel The equivalent channel formed after multiplication There will be multiple discontinuities, and the channel estimated at the UE is... In discontinuous channel conditions, channel estimation smoothing and denoising will be problematic, which will have a significant impact on the performance of data equalization. Figure 4 The blue line in the middle represents the area that has not been processed. The red line represents the real part of the smoothed equivalent channel response, while the red line represents the real part of the smoothed equivalent channel response. As you can see, the red line is relatively smooth.

[0126] It should be noted that, since there may be multiple subcarriers, the above implementation yields a corresponding precoding matrix, W, for each subcarrier. 11 In other words, the terminal ultimately obtains the precoding matrix of the first antenna element for the terminals associated with it based on the feedback equivalent channel matrix.

[0127] Optionally, the specific implementation of performing polynomial compression on the precoding matrix to obtain the feedback result includes:

[0128] The feedback result is obtained based on the precoding matrix and the length of the subcarrier block.

[0129] Optionally, in one implementation, the specific implementation of obtaining the feedback result based on the precoding matrix and the length of the subcarrier-blocked block includes:

[0130] The first matrix is ​​obtained based on the length of the subcarrier-divided block and the degree of the polynomial.

[0131] Based on the first matrix and the pre-encoding matrix, obtain the fitting parameters;

[0132] The fitted parameters are determined as the feedback result.

[0133] Optionally, the number of columns in the first matrix is ​​determined based on the degree of the polynomial, and the number of rows in the first matrix is ​​determined based on the length of the subcarrier block.

[0134] Optionally, the degree of the polynomial and the length of the subcarrier block can be determined by the network side and notified to the terminal, or the terminal can determine them and notify the network side (i.e., the second antenna unit, which can then notify the first antenna unit).

[0135] It should be noted that, in the context of After smoothing, the precoding matrix on adjacent subcarriers on the same OFDM symbol can be viewed as a combination of multiple linear or quadratic terms of the channel response, such as... Figure 5 As shown.

[0136] If the length of the selected subcarrier block (which can be understood as the number of subcarriers contained in the block, denoted by L; optionally, subcarrier blocking can also be understood as grouping subcarriers) is relatively small, the subcarrier envelopes of the real and imaginary parts of the channel within a selected block are generally linear, for example... Figure 6 One piece, L=5;

[0137] Assuming each block consists of 5 subcarriers, the entire system can be approximated as a synthesis of the frequency response of multiple such linear segments. After dividing the subcarriers of an OFDM symbol into blocks, the frequency domain response lies in a selected segment. As long as the number of subcarriers L in the selected segment is appropriate, each segment can be approximated as the envelope of a straight line, a quadratic, or a cubic curve. Taking a straight line as an example, an element in the precoding matrix can be approximated in the frequency domain as: The x-axis represents the index of a subcarrier selected within a block. For example, a block with a length of 5: In matrix form, it can be represented as:

[0138] .

[0139] Since the precoding matrix has already been calculated on the terminal side, the UE can use the linear relationship of the precoding matrix within the segment to calculate its linear fitting coefficients a and b (i.e., the feedback results mentioned above), such as: Since A (corresponding to the first matrix mentioned above) is known and is a constant, then It can also be calculated in advance, and it is a fixed value, so there is no need for real-time calculation. Taking the case where the block length is 5 as an example again, The calculation is as follows:

[0140] .

[0141] For the terminal and RRU sides, with the block length determined... All of this is already known, so we only need to send... The matrix can then be used to recover H, that is, to recover the precoding matrix. In the case of linear fitting, a block only needs to send two complex numbers.

[0142] Restoring the precoding matrix on the RRU side only requires performing... The operation yields the precoding matrices for downlink transmission, thus recovering the precoding matrix on each subcarrier. It's important to note that since the terminal can only communicate with its associated second antenna unit, only the second antenna unit receives the feedback result. However, the first antenna unit actually uses this feedback result. Therefore, the second antenna unit can send the feedback result to the control unit (which can be understood as a module located at a higher layer that controls the first and second antenna units). The control unit then determines the precoding matrix and sends it to the first antenna unit. Alternatively, the second antenna unit can directly send the feedback result to the first antenna unit, which then determines the precoding matrix. After obtaining the precoding matrix, the first antenna unit can send downlink information to its associated terminals based on this matrix, thus preventing interference from the information sent by the first antenna unit to the terminals associated with the second antenna unit.

[0143] Optionally, the specific implementation of the control unit or the first antenna unit obtaining the precoding matrix based on the feedback result includes:

[0144] The first matrix is ​​obtained based on the length of the subcarrier-divided block and the degree of the polynomial.

[0145] Based on the first matrix and the feedback result, obtain the precoding matrix.

[0146] Optionally, the process of fitting an element in the terminal compression precoding matrix is ​​illustrated in the flowchart below. Figure 7 As shown, Nt is the number of transmitting antennas.

[0147] The above discussion focuses on linear fitting compression of an element in a precoding matrix. In a MIMO system, if the transmitter has... One antenna, transmitting end sends There are 10 streams, then there are a total of 10 streams. Each channel needs to perform the aforementioned operations, namely Figure 7 The process in the middle.

[0148] At the sending and receiving ends, and The length L of the dependent block is a fixed value. It can be stored in a fixed table according to the selected length. It does not need to be calculated in real time. When the feedback result corresponding to the precoding matrix is ​​fed back, L can be informed to the terminal by using control signaling to select A. Generally, L reports one value on one OFDM subcarrier.

[0149] Optionally, in scenarios with strong frequency selectivity, where the channel response in the frequency domain has poor linearity, it can be approximated using a binomial or higher-order polynomial. Taking a quadratic term block length of 5 as an example: The corresponding block fit can be represented in matrix form as follows:

[0150] .

[0151] .

[0152] The terminal only needs to send The three complex values ​​(i.e., the feedback result mentioned above, which includes three fitting parameters) can be used to reduce the precoding matrix estimate on the RRU side to... .

[0153] The general expression for polynomial fitting assumes that the polyphase used is of degree m and the block length is L. Then, a more general expression for A can be derived based on the parity of L as follows:

[0154] Even number case:

[0155] .

[0156] Odd number cases:

[0157] .

[0158] With m selected, the number of columns in A is fixed, while the number of rows in A is related to L, and the construction of A differs depending on whether it is odd or even. With A fixed, It is now determined that, on the terminal side, the result can be calculated based on the pairing condition of (m,L). And store it as a table, which saves on calculations.

[0159] In the polynomial case, L can be chosen to be a longer value, usually up to 3 RBs. In a 3*RB case, with 36 subcarriers, 36 complex values ​​need to be sent. In the binomial case, it can be compressed to 3 / 36 of the original data to be transmitted.

[0160] For the same length L, binomial fitting generally performs better than linear fitting, and trinomial compression performs better than binomial fitting. Therefore, the higher the polynomial dimension, the longer the length of L can be, and the higher the compression efficiency.

[0161] like Figure 8 As shown, the signal-to-interference plus-noise ratio (SINR) obtained using the polynomial compression technique described in this application is comparable to the ideal SINR. The SINR values ​​of the feedback are almost identical, indicating that the performance difference between the polynomial feedback and the ideal feedback is very small.

[0162] The embodiments of this application can achieve the following beneficial effects:

[0163] 1. This application can achieve a near-zero interference coordination scheme for multi-user D-MIMO deployment. Compared with the precoding scheme of joint RRU coordination, the performance difference is small. However, the embodiments of this application avoid the strict synchronization and calibration requirements between RRUs required by the RRU coordination scheme.

[0164] 2. By utilizing CSI-RS channels or other forms of common channels, combined with precoding matrix generation methods, and smoothing and novel precoding matrix compression feedback methods, the compression ratio of precoding matrix feedback is improved. Compared with the codebook-based or Beamforming weight V compression feedback algorithms in 5G NR or Wi-Fi standards, the compression ratio in this application is higher, greatly reducing the feedback bandwidth requirements. Furthermore, the precoding performance in this application is significantly improved compared to the codebook-based feedback performance in the original 5G standard.

[0165] like Figure 9 As shown, an embodiment of this application provides a multi-user interference suppression method applied to a second antenna unit, comprising:

[0166] Step 901: Receive feedback results sent by the terminal. The feedback results are obtained by the terminal performing polynomial compression on the precoding matrix. The precoding matrix is ​​obtained by performing singular value decomposition on the feedback equivalent channel matrix of the interference of the terminal by the first antenna element, and smoothing the right singular value matrix obtained by carrier dimension.

[0167] Step 902: Based on the feedback result, communicate with the first antenna unit so that the first antenna unit transmits downlink information based on the precoding matrix obtained through the feedback result.

[0168] It should be noted that all the implementation methods in the above embodiments are applicable to the multi-user interference suppression method applied to the second antenna unit side, and can achieve the same technical effect, so they will not be described again here.

[0169] like Figure 10 As shown, a multi-user interference suppression device 1000 according to an embodiment of this application is applied to a terminal and includes:

[0170] The first acquisition module 1001 is used to acquire the feedback equivalent channel matrix of the interference of the first antenna element to the terminal;

[0171] The second acquisition module 1002 is used to perform singular value decomposition on the feedback equivalent channel matrix and perform carrier dimension smoothing on the right singular vector matrix obtained by decomposition to obtain a precoding matrix.

[0172] The third acquisition module 1003 is used to perform polynomial compression on the precoding matrix and obtain feedback results;

[0173] The first sending module 1004 is used to send the feedback result to the network device.

[0174] Optionally, the first acquisition module 1001 is configured to:

[0175] Based on the first signal received from the first antenna element, obtain the first channel matrix between the first antenna element and the terminal;

[0176] Based on the second signal received from the second antenna unit, obtain the second channel matrix between the second antenna unit and the terminal;

[0177] Based on the first channel matrix and the second channel matrix, obtain the feedback equivalent channel matrix of the interference of the first antenna element to the terminal.

[0178] Optionally, the specific implementation of obtaining the feedback equivalent channel matrix of the interference of the first antenna element to the terminal based on the first channel matrix and the second channel matrix includes:

[0179] Perform singular value decomposition on the second channel matrix to obtain the left singular value matrix;

[0180] Based on the singular value left matrix and the first channel matrix, the feedback equivalent channel matrix of the interference of the first antenna element to the terminal is obtained.

[0181] Optionally, the device further includes:

[0182] The second receiving module is used to receive first information sent by the second antenna unit, the first information being used to indicate an antenna port group associated with the terminal, the antenna port group corresponding to the second antenna unit.

[0183] Optionally, the third acquisition module 1003 is used for:

[0184] The feedback result is obtained based on the precoding matrix and the length of the subcarrier block.

[0185] Optionally, the specific implementation of obtaining the feedback result based on the precoding matrix and the length of the subcarrier-blocked block includes:

[0186] The first matrix is ​​obtained based on the length of the subcarrier-divided block and the degree of the polynomial.

[0187] Based on the first matrix and the pre-encoding matrix, obtain the fitting parameters;

[0188] The fitted parameters are determined as the feedback result.

[0189] Optionally, the number of columns in the first matrix is ​​determined based on the degree of the polynomial, and the number of rows in the first matrix is ​​determined based on the length of the subcarrier block.

[0190] It should be noted that this device embodiment corresponds one-to-one with the above method embodiments. All implementation methods in the above method embodiments are applicable to this device embodiment and can achieve the same technical effect.

[0191] Another embodiment of this application provides a multi-user interference suppression device, for example, the multi-user interference suppression device is a terminal, such as... Figure 11 As shown, it includes a transceiver 1110, a processor 1100, a memory 1120, and a program or instructions stored in the memory 1120 and executable on the processor 1100; when the processor 1100 executes the program or instructions, it implements the above-mentioned multi-user interference suppression method.

[0192] The transceiver 1110 is used to receive and send data under the control of the processor 1100.

[0193] Among them, Figure 11In this context, the bus architecture can include any number of interconnected buses and bridges, specifically linking various circuits of one or more processors represented by processor 1100 and memory represented by memory 1120 together. The bus architecture can also link various other circuits such as peripheral devices, voltage regulators, and power management circuits, which are well known in the art and therefore will not be described further herein. The bus interface provides an interface. Transceiver 1110 can be multiple elements, including transmitters and receivers, providing a unit for communicating with various other devices over a transmission medium. For different user equipment, user interface 1130 can also be an interface capable of connecting external or internal devices, including but not limited to keypads, displays, speakers, microphones, joysticks, etc.

[0194] The processor 1100 is responsible for managing the bus architecture and general processing, and the memory 1120 can store the data used by the processor 1100 when performing operations.

[0195] like Figure 12 As shown, an embodiment of this application discloses a multi-user interference suppression device 1200, applied to a second antenna unit, comprising:

[0196] The first receiving module 1201 is used to receive feedback results sent by the terminal. The feedback results are obtained based on the terminal performing polynomial compression on the precoding matrix. The precoding matrix is ​​obtained based on the first antenna element performing singular value decomposition on the feedback equivalent channel matrix of the interference of the terminal. The carrier dimension is smoothed on the right singular value matrix obtained by decomposition.

[0197] The second transmitting module 1202 is used to communicate with the first antenna unit based on the feedback result, so that the first antenna unit transmits downlink information based on the precoding matrix obtained through the feedback result.

[0198] It should be noted that this device embodiment corresponds one-to-one with the above method embodiments. All implementation methods in the above method embodiments are applicable to this device embodiment and can achieve the same technical effect.

[0199] Another embodiment of this application describes a multi-user interference suppression device, for example, a second antenna unit. Figure 13 As shown, it includes a transceiver 1310, a processor 1300, a memory 1320, and a program or instructions stored in the memory 1320 and executable on the processor 1300; when the processor 1300 executes the program or instructions, it implements the above-mentioned multi-user interference suppression method.

[0200] The transceiver 1310 is used to receive and send data under the control of the processor 1300.

[0201] Among them, Figure 13 In this context, the bus architecture may include any number of interconnected buses and bridges, specifically linking various circuits together, represented by one or more processors (processor 1300) and memory (memory 1320). The bus architecture may also link together various other circuits such as peripheral devices, voltage regulators, and power management circuits, which are well known in the art and therefore will not be described further herein. The bus interface provides an interface. The transceiver 1310 may be multiple elements, including transmitters and receivers, providing a unit for communicating with various other devices over a transmission medium. The processor 1300 is responsible for managing the bus architecture and general processing, and the memory 1320 may store data used by the processor 1300 during operation.

[0202] This application provides a readable storage medium storing a program or instructions. When executed by a processor, the program or instructions implement the steps in the multi-user interference suppression method described above and achieve the same technical effect. To avoid repetition, further details are omitted here. The computer-readable storage medium may include read-only memory (ROM), random access memory (RAM), magnetic disk, or optical disk.

[0203] It should be further noted that the terminals described in this specification include, but are not limited to, smartphones, tablets, etc., and many of the functional components described are referred to as modules in order to emphasize the independence of their implementation.

[0204] In this embodiment, the module can be implemented in software so that it can be executed by various types of processors. For example, an identified executable code module may include one or more physical or logical blocks of computer instructions, which may be constructed as objects, procedures, or functions. Nevertheless, the executable code of the identified module does not need to be physically located together, but may include different instructions stored in different bits, which, when logically combined, constitute the module and achieve the module's intended purpose.

[0205] In practice, an executable code module can be a single instruction or many instructions, and can even be distributed across multiple different code segments, different programs, and across multiple memory devices. Similarly, operational data can be identified within the module and can be implemented in any suitable form and organized within any suitable data structure. This operational data can be collected as a single dataset or distributed across different locations (including different storage devices), and can exist, at least in part, solely as electronic signals within the system or network.

[0206] When a module can be implemented using software, considering the current level of hardware technology, modules that can be implemented in software can be implemented using hardware circuits by those skilled in the art to achieve the corresponding functions, without considering cost. These hardware circuits include conventional very-large-scale integrated circuits (VLSI) or gate arrays, as well as existing semiconductors such as logic chips and transistors, or other discrete components. Modules can also be implemented using programmable hardware devices, such as field-programmable gate arrays, programmable array logic, and programmable logic devices.

[0207] The exemplary embodiments described above are with reference to the accompanying drawings. Many different forms and embodiments are feasible without departing from the spirit and teachings of this application. Therefore, this application should not be construed as limiting the exemplary embodiments set forth herein. Rather, these exemplary embodiments are provided to make this application complete and convey the scope of this application to those skilled in the art. In these drawings, component dimensions and relative dimensions may be exaggerated for clarity. The terminology used herein is for the purpose of describing particular exemplary embodiments only and is not intended to be limiting. As used herein, unless clearly indicated otherwise, the singular forms “a,” “an,” and “the” are intended to include all such forms. It will be further understood that the terms “comprising” and / or “including”, when used in this specification, indicate the presence of the stated features, integers, steps, operations, components, and / or elements, but do not exclude the presence or addition of one or more other features, integers, steps, operations, components, and / or groups thereof. Unless otherwise indicated, when stated, a range of values ​​includes the upper and lower limits of the range and any subranges in between.

[0208] The above description is the preferred embodiment of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principles described in this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A multi-user interference mitigation method, characterized by, The method comprises: obtaining a feedback equivalent channel matrix of interference of a first antenna unit on a terminal; performing singular value decomposition on the feedback equivalent channel matrix, and performing carrier dimension smoothing on a singular value right matrix obtained by the decomposition to obtain a precoding matrix; performing polynomial compression on the precoding matrix to obtain a feedback result; sending the feedback result to a second antenna unit.

2. The method of claim 1, wherein, The method comprises: obtaining a first channel matrix between the first antenna unit and the terminal according to a first signal sent by the first antenna unit; obtaining a second channel matrix between the second antenna unit and the terminal according to a second signal sent by the second antenna unit; obtaining a feedback equivalent channel matrix of interference of the first antenna unit on the terminal according to the first channel matrix and the second channel matrix.

3. The method of claim 2, wherein, The method comprises: performing singular value decomposition on the second channel matrix to obtain a singular value left matrix; obtaining a feedback equivalent channel matrix of interference of the first antenna unit on the terminal according to the singular value left matrix and the first channel matrix.

4. The method of claim 2, wherein, The method further comprises: receiving first information sent by the second antenna unit, the first information being used to indicate an antenna port group associated with the terminal, the antenna port group corresponding to the second antenna unit.

5. The method of claim 1, wherein, The method comprises: obtaining a feedback result based on the precoding matrix and the length of the block after subcarrier blocking.

6. The method of claim 5, wherein, The method comprises: obtaining a first matrix based on the length of the block after subcarrier blocking and the degree of the polynomial; obtaining fitting parameters according to the first matrix and the precoding matrix; determining the fitting parameters as the feedback result.

7. The method of claim 6, wherein, The number of columns of the first matrix is determined based on the degree of the polynomial, and the number of rows of the first matrix is determined based on the length of the block after subcarrier blocking.

8. A multi-user interference mitigation method, characterized by, The method comprises: receiving a feedback result sent by the terminal, the feedback result being obtained based on polynomial compression of a precoding matrix by the terminal, the precoding matrix being obtained based on singular value decomposition of a feedback equivalent channel matrix of interference of a first antenna unit on the terminal, and carrier dimension smoothing on a singular value right matrix obtained by the decomposition; communicating with the first antenna unit based on the feedback result, so that the first antenna unit sends downlink information based on the precoding matrix obtained through the feedback result.

9. A multi-user interference mitigation apparatus, characterized by, The method comprises: a first obtaining module, configured to obtain a feedback equivalent channel matrix of interference of a first antenna unit on a terminal; a second obtaining module, configured to perform singular value decomposition on the feedback equivalent channel matrix, and perform carrier dimension smoothing on a singular value right matrix obtained by the decomposition to obtain a precoding matrix; a third obtaining module, configured to perform polynomial compression on the precoding matrix to obtain a feedback result; a first sending module, configured to send the feedback result to a network device.

10. A multi-user interference mitigation method apparatus characterized by, The method comprises: The first receiving module is configured to receive a feedback result sent by a terminal, wherein the feedback result is obtained based on polynomial compression of a precoding matrix, and the precoding matrix is obtained based on singular value decomposition of a feedback equivalent channel matrix of interference of the terminal on the first antenna unit, and a singular value right matrix obtained by the decomposition is subjected to carrier dimension smoothing processing to obtain; The second sending module is configured to communicate with the first antenna unit based on the feedback result, so that the first antenna unit sends downlink information based on the precoding matrix obtained through the feedback result.

11. A multi-user interference mitigation method apparatus comprising: A transceiver, a processor, a memory, and a program or instructions stored on the memory and executable on the processor; characterized by, when the processor executes the program or instructions, the processor implements the multi-user interference suppression method of any one of claims 1-8.

12. A readable storage medium, on which a program or instructions are stored, characterized in that, The program or instructions are executed by the processor to implement the steps in the multi-user interference suppression method of any one of claims 1-8.

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