Method and system for maximizing signal-to-leakage ratio for a skywave massive MIMO beam structure precoding

Abstract

The application discloses a method and system for maximizing signal-to-leakage-and-noise ratio (SLNR) of a sky-wave massive MIMO beam structure precoding, and relates to a sky-wave massive MIMO beam structure precoding based on an average SLNR maximization criterion and an instantaneous SLNR maximization criterion. The application utilizes the sparsity of a sky-wave massive MIMO downlink channel in a beam domain to generate a non-zero beam index set of each user, and utilizes a spatial beam selection matrix to extract beam domain statistical / instantaneous channel information to obtain a dimension-reduced beam domain channel vector of each user; based on the dimension-reduced beam domain channel vector of each user, a beam domain precoder based on the average SLNR or the instantaneous SLNR maximization criterion is designed, and thus signal precoding transmission for maximizing the SLNR is performed. Experiments show that when the number of base station antennas and the number of users are large, the application can significantly reduce the complexity of precoding while ensuring the performance of a sky-wave massive MIMO precoder and rate.

Description

Technical Field

[0001] This invention belongs to the field of communication technology and relates to a precoding method and system for skywave massive MIMO beamstructure with maximum signal-to-leakage-to-noise ratio (SNR). Specifically, it relates to a precoding method and system for skywave massive MIMO beamstructure based on the average SNR maximization criterion and the instantaneous SNR maximization criterion. Background Technology

[0002] Skywave communication is an effective medium- to long-distance communication method, typically operating in the 3-30MHz electromagnetic frequency band. Electromagnetic waves in this band can be reflected by the ionosphere, achieving long-distance communication over distances exceeding 3000 kilometers. Skywave communication does not require expensive additional communication equipment, thus offering advantages over satellite communication such as lower cost and higher robustness. However, the time-varying nature of skywave channels, the complexity of ionospheric motion, and the limited bandwidth restrict the data transmission rate of point-to-point skywave communication.

[0003] To improve the channel capacity of skywave communication, massive MIMO technology is introduced. Massive MIMO is one of the key communication technologies widely used in fifth-generation cellular wireless communication. By equipping the base station with a large-scale array antenna, it can serve a large number of users simultaneously, thereby improving the spectral efficiency and power efficiency of communication.

[0004] With the increasing number of base station antennas and the number of users served, massive MIMO faces many challenges, among which precoding is a typical one. In massive MIMO multi-user downlink communication, the base station uses the same time-frequency resources to communicate with multiple users, causing co-channel interference—that is, interference caused by other users on the same channel for the user of interest. In massive MIMO communication systems, the antenna dimension is high, so existing precoding methods are often highly complex, such as those based on the minimum mean square error criterion, the zero-forcing criterion, and the maximum signal-to-interference-plus-noise ratio criterion. Therefore, designing a low-complexity precoder is of great significance. Summary of the Invention

[0005] Purpose of the invention: The purpose of this invention is to provide a precoding method for skywave massive MIMO beam structure based on the signal-to-leakage-to-noise ratio maximization criterion, so as to solve the technical problem of how to design and implement a low-complexity precoder based on the skywave massive MIMO beam-based channel model and using beam domain channel information.

[0006] Technical Solution: To achieve the above-mentioned objectives, the specific technical solution of this invention is as follows:

[0007] A skywave massive MIMO beamstructure precoding method based on the average signal-to-noise ratio maximization criterion includes:

[0008] The transformation between spatial domain and beam domain channels is achieved through the beam matrix V. Taking advantage of the sparsity of the downlink channel in the beam domain of skywave massive MIMO, the non-zero beam indices occupied by user u are denoted as a set. And utilize the space beam selection matrix Statistical channel information in the beam domain Extraction is performed to obtain the reduced-dimensional beam domain statistical channel information for each user. in B represents the number of beam sampling points. u This indicates the number of non-zero beams occupied by user u. Represents a set Elements from smallest to largest express The b-th dimension of the identity matrix u,i List;

[0009] Using reduced-dimensional beam domain statistical channel information, an optimization problem maximizing the average signal-to-noise ratio is formed, and the beam domain precoder w for each user is obtained by solving the problem. u ;

[0010] The beam domain precoder for each user w u Send signal x with user u Multiplying these signals yields the precoded signals for each user's beam domain. Then, beam mapping is performed, and the summation of the precoded signals for each user's beam domain after beam mapping is obtained. Where U represents the number of users;

[0011] Multiplying the beam matrix by the summation result yields... Implement precoding of user signals.

[0012] Furthermore, the beam matrix V k A matrix consisting of a set of rudder vectors after uniformly sampling the direction cosines; beam domain statistical channel information. Let be the beam domain channel coupling vector for user u.

[0013] Furthermore, the user u occupies the beam index set. The set consisting of the beam position indices of the non-zero elements of the user's u-beam domain channel; the reduced-dimensional beam domain statistical channel information. Statistical channel information for user u-beam domain Using the space beam selection matrix N u The vector formed by the extracted non-zero beam set position elements; the beam mapping is performed using the spatial beam selection matrix N. u The precoded signals of each user's beam domain are mapped to the positions occupied by the non-zero beams of that user in all beam indices according to the non-zero beam index.

[0014] Furthermore, the average signal-to-leakage-to-noise ratio maximization optimization problem is formulated as follows:

[0015]

[0016]

[0017] In the formula, For user u's beam domain precoder, P u For power constraints, Let represent the noise power of user u. The superscript H indicates the conjugate transpose of a matrix or vector, and diag{a} represents a diagonal matrix with vector a as its diagonal element.

[0018] The steps for solving the optimization problem include:

[0019] calculate And perform Cholesky decomposition

[0020] calculate

[0021] calculate

[0022] calculate And perform eigenvalue decomposition

[0023] Calculate the beam domain precoder for user u in To make w u Scaling factor that satisfies power constraints; where B u The first column of the 1-dimensional identity matrix.

[0024] A skywave massive MIMO beamstructure precoding method based on the instantaneous signal-to-leakage-to-noise ratio maximization criterion includes:

[0025] The transformation between the spatial domain and the beam domain is achieved through the beam matrix V. Taking advantage of the sparsity of the downlink channel in the beam domain of skywave massive MIMO, the non-zero beam indices occupied by user u are denoted as a set. And utilize the space beam selection matrix For beam domain channel vector Extraction is performed to obtain the reduced-dimensional beam domain channel vector for each user.

[0026] Using reduced-dimensional beam domain channel vectors This leads to an optimization problem that maximizes the signal-to-leakage-to-noise ratio using instantaneous channel information. Solving this problem yields the beam domain precoder w for each user. u ;

[0027] The beam domain precoder for each user w u Send signal x with user u Multiplying these signals yields the precoded signals for each user's beam domain, which are then used in conjunction with the spatial beam selection matrix N. u Beam mapping is performed, and the precoded signals of each user's beam domain after beam mapping are summed to obtain...

[0028] Multiplying the beam matrix by the summation result yields... Implement precoding of user signals.

[0029] Furthermore, the beam matrix V k The matrix is ​​a set of rudder vectors uniformly sampled from the direction cosines; the beam domain channel vector It is a random vector in which each element is independent and non-uniformly distributed, and each element is the beam domain channel coefficient of user u of the k-th subcarrier in the n-th OFDM symbol at each beam position.

[0030] Furthermore, the user u occupies the beam index set. The set of beam position indices for the non-zero elements of the user's beam domain channel; the reduced-dimensional beam domain channel vector User u-beam domain channel vector Using the space beam selection matrix N u Extract the vector formed by the non-zero beam set position elements; the beam mapping is performed using the spatial beam selection matrix N. u The precoded signals of each user's beam domain are mapped to the positions occupied by the non-zero beams of that user in all beam indices according to the non-zero beam index.

[0031] Furthermore, the optimization problem of maximizing the signal-to-leakage-to-noise ratio using instantaneous channel information is formulated as follows:

[0032]

[0033]

[0034] In the formula, For user u's beam domain precoder, P u For power constraints, This represents the noise power of user u.

[0035] The steps for solving the optimization problem include:

[0036] calculate

[0037] calculate Where γ is the value that makes w uA power scaling factor that satisfies power constraints.

[0038] A computer system includes a memory, a processor, and a computer program / instructions stored in the memory and executable on the processor. When executed by the processor, the computer program / instructions implement the steps of the skywave massive MIMO beamform precoding method based on the average signal-to-noise ratio maximization criterion, or implement the steps of the skywave massive MIMO beamform precoding method based on the instantaneous signal-to-noise ratio maximization criterion.

[0039] A computer program product includes a computer program / instructions that, when executed by a processor, implement the steps of the skywave massive MIMO beamstructure precoding method based on the average signal-to-noise ratio maximization criterion, or implement the steps of the skywave massive MIMO beamstructure precoding method based on the instantaneous signal-to-noise ratio maximization criterion.

[0040] Beneficial Effects: This invention considers that the signal-to-leakage-to-noise ratio (SNR) maximization criterion can make the precoder design optimization problem a non-user-coupled optimization problem, thus obtaining a closed-form solution. The beam-based channel model of skywave MIMO exhibits significant sparsity in the beam domain channel vector. Utilizing the sparsity of the beam domain channel in precoder design can effectively reduce complexity. This invention provides a skywave MIMO precoding method based on SNR, which has the following advantages compared to existing technologies: 1. This invention introduces a beam-based channel model, which can more accurately represent the spatial domain channel; and because the downlink channel of skywave MIMO exhibits sparse characteristics in the beam domain, this sparsity can be used to reduce the dimensionality of the optimization problem, thereby reducing the complexity of skywave MIMO downlink precoding that maximizes SNR. 2. This invention proposes a skywave MIMO beam structure precoding method based on average SNR. Experiments show that when the number of base station antennas is large, the precoder design complexity can be effectively reduced while ensuring precoder performance. 3. This invention proposes a skywave large-scale MIMO beam structure precoding method based on instantaneous signal-to-noise ratio. Experiments show that when the number of base station antennas is large, the design complexity of the precoder can be effectively reduced while ensuring the performance of the precoder. Attached Figure Description

[0041] Figure 1 This is a schematic diagram of the precoding method for skywave massive MIMO beam structure according to an embodiment of the present invention;

[0042] Figure 2 This is a flowchart of the design of a skywave massive MIMO beam domain precoder based on the maximization criterion of average signal-to-noise ratio or instantaneous signal-to-noise ratio, according to an embodiment of the present invention.

[0043] Figure 3 This is a comparison chart of the sum and rate performance of the precoder based on the average signal-to-noise ratio maximization criterion under different total transmit power conditions with different base station antenna numbers in the embodiments of the present invention;

[0044] Figure 4 This is a comparison chart of the sum and rate performance of the precoder based on the instantaneous signal-to-noise ratio maximization criterion under different total transmit power conditions with different base station antenna numbers in the embodiments of the present invention. Detailed Implementation

[0045] To better understand the purpose, structure, and function of this invention, the following detailed description of the skywave large-scale MIMO precoding method based on signal-to-leakage-to-noise ratio, with reference to the accompanying drawings, is provided.

[0046] See Figure 1 This invention discloses a schematic diagram of the skywave massive MIMO precoding process. The base station is configured with a massive MIMO antenna array, which communicates with a large number of user terminals within its coverage area via ionospheric reflection. The skywave massive MIMO precoding method mainly involves two aspects: the design of the precoder and the implementation of signal precoding.

[0047] See Figure 2 This invention provides two design methods for skywave massive MIMO precoders based on the signal-to-leakage-to-noise ratio maximization criterion. These methods are primarily applicable to skywave massive MIMO communication systems where base stations are equipped with massive antenna arrays to simultaneously serve a large number of single-antenna users. Specifically, the methods include:

[0048] Through beam matrix V k To achieve the transformation between the spatial domain and the beam domain, the sparsity of the downlink channel in the skywave massive MIMO in the beam domain is utilized, and the non-zero beam index occupied by user u is denoted as a set. For a skywave large-scale MIMO beam-domain precoder based on average signal-to-noise ratio, the spatial beam selection matrix is ​​utilized. Statistical channel information in the beam domain Extraction is performed to obtain the reduced-dimensional beam domain statistical channel information for each user. in B represents the number of beam sampling points. u This indicates the number of non-zero beams occupied by user u. Represents a set Elements from smallest to largest express The b-th dimension of the identity matrix u,i For a skywave massive MIMO beamdomain precoder based on instantaneous signal-to-noise ratio, the spatial beam selection matrix is ​​utilized. For beam domain channel vector Extraction is performed to obtain the reduced-dimensional beam domain channel vector for each user.

[0049] For a skywave massive MIMO beam-domain precoder based on average signal-to-leakage-noise ratio (SNR), the average SNR maximization optimization problem is formed by using the reduced-dimensional beam-domain statistical channel vector. The beam-domain precoder for each user is then obtained by multiplying the precoder of each user with the transmitted signal to obtain the precoded signal of each user. Beam mapping is then performed, and the precoded signals of each user after beam mapping are summed. Finally, the beam matrix is ​​multiplied by the summation result to achieve precoding of the user signal.

[0050] For a skywave massive MIMO beam-domain precoder based on instantaneous signal-to-leakage-noise ratio (SNR), the beam-domain precoder for each user is obtained by solving the SNR maximization optimization problem using instantaneous channel information through reduced-dimensional beam-domain channel vector formation. The beam-domain precoder for each user is then multiplied with the user's transmitted signal to obtain the user's beam-domain precoded signal. Beam mapping is then performed, and the beam-mapped user beam-domain precoded signals are summed. Finally, the beam matrix is ​​multiplied with the summation result to achieve precoding of the user signal.

[0051] The method of this invention is mainly applicable to skywave massive MIMO systems equipped with large-scale antenna arrays on the base station side to simultaneously serve multiple users. The specific implementation process of the precoding method involved in this invention will be described in detail below with reference to a specific communication system example. It should be noted that this invention is not only applicable to the specific system model described in this embodiment, but also to other configured system models.

[0052] I. System Configuration

[0053] In this embodiment, a skywave massive MIMO-OFDM system operating in TDD mode is considered. The base station is equipped with a uniform linear array of M antennas. The transmitted signal is reflected by the E and F layers of the ionosphere, simultaneously serving U single-antenna users. Let N... c N g N v Let and Δf represent the number of subcarriers, the cyclic prefix length (CP), the number of effective subcarriers, and the subcarrier spacing, respectively. Therefore, the OFDM symbol spacing is T. sym =(N c +N g ) / (N c Δf). The transmission frame structure is set as follows: each frame includes N OFDM symbols, where the first... The first symbol represents the uplink data symbol, followed by a single uplink training symbol. Finally... The symbols represent downlink data symbols.

[0054] In skywave communication systems, due to the complex ionospheric environment, the carrier frequency f c The required frequency needs to change accordingly, therefore the highest system operating frequency is defined as f. o Unlike traditional massive MIMO communication, the spacing between adjacent antennas is d = λ. o / 2, where λ o =c / f o λ is the wavelength, and c is the speed of light.

[0055] II. Beam-based Channel Model

[0056] During downlink (DL) transmission, let the signal transmitted to the u-th user on the k-th subcarrier of the n-th symbol be denoted as . The demodulated signal corresponding to the receiving end is

[0057]

[0058] in, For user u, additive white Gaussian noise, The frequency domain channel impulse response of user u can be expressed as:

[0059]

[0060] in

[0061]

[0062]

[0063] Where L u β is the path length from user u to the base station, Δτ = d / c. u,p , φ u,p , τ u,p and Ω u,p Let represent gain, initial phase, Doppler frequency, transmission delay to the first antenna of the base station, and direction cosine of the p-th path, respectively. The rudder vector pointing to Ω on the k-th subcarrier is defined as...

[0064]

[0065] Note that due to the spatial broadband effect, the rudder vector varies with different subcarriers, thus the spatial domain channel vector... It can be represented as

[0066]

[0067] in

[0068] To characterize the channel in the beam domain, the direction cosines are uniformly sampled. in It is the number of sampling points. and Define a set It includes the direction cosines of all paths of user u. Therefore, h u,n,k It can be approximated as

[0069]

[0070] in For sampling rudder vectors, and Each sampling rudder vector corresponds to a beam in the spatial domain, and all users share the same set of sampling rudder vectors. Therefore, it is called a beam-based channel model. The beam domain channel vector and V k This is referred to as the beam matrix of the k-th subcarrier. In skywave massive MIMO channels, the angular spread from each user to the base station is typically small, resulting in high sparsity of the beam domain channel vector.

[0071] Define channel coupling vector This represents statistical channel information. Note that statistical channel information is only related to the user and not to the subcarrier. Let the index of the non-zero element of the beam domain channel vector be the set... And record the number of non-zero beams occupied by user u as Define a set The number of non-zero beams occupied by all users can be expressed as: Set All elements in the array, from smallest to largest, are as follows: Then a space beam selection matrix can be defined.

[0072]

[0073] By extracting the channel coupling vector using the spatial beam selection matrix N, we can obtain the dimensionless spatial beam domain statistical channel information corresponding to the beam positions occupied by all users, denoted as . It can also be used for beam matrix V k Extraction is performed to obtain the dimension-reduced beam matrix corresponding to the beam positions occupied by all users, denoted as... For user u, let the set be... All elements in the array are denoted as follows, from smallest to largest: Then a space beam selection matrix can be defined.

[0074]

[0075] in express The b-th dimension of the identity matrix u,i Column. Using the space beam selection matrix N uBy extracting the data, we can obtain the reduced-dimensional spatial beam domain statistical channel information corresponding to the beam position occupied by user u, i.e. It is also possible to adjust the beam matrix V k Extraction is performed to obtain the reduced-dimensional beam matrix corresponding to the beam position occupied by user u, denoted as

[0076] III. A Skywave Large-Scale MIMO Beam Structure Precoding Method Based on Average Signal-to-Noise Ratio

[0077] Assume the base station has perfect statistical channel information, and we are concerned with the downlink transmission precoding problem of the k-th subcarrier of the n-th OFDM symbol. For simplicity, the subscripts n and k are omitted below. Note that (1) can be rewritten as

[0078]

[0079] Where p u It is the pre-encoder for user u, satisfying the power constraint. x u It is a data symbol with zero mean and unit variance sent to user u.

[0080] The average signal-to-noise ratio (SNR) for user u is defined as the ratio of the expected signal energy intended to be transmitted to the expected signal energy and noise energy leaked to other users. The expression for the average SNR is:

[0081]

[0082] This leads to the problem of maximizing the average signal-to-noise ratio in precoding.

[0083]

[0084] Define the beam domain precoding vector q u =N T V H p u The average signal-to-noise ratio can be rewritten as

[0085]

[0086] Abbreviated as A = N T V H (N T V H ) + -I, G=(N T V H VN) + Therefore, for any vector Make a = N T V H b is established and The necessary and sufficient condition for its existence is Aa = 0. Therefore, if q u Satisfy Aq u =0 and q u =N T V H p u Then the pre-encoder p u It always exists. At this point, the solution to optimization problem (12) satisfies in

[0087]

[0088] Further assuming the number of users is finite, and the direction cosines of each user are discrete and finite. As M approaches infinity, we have... Further and At this point, the optimal solution expression becomes in The optimal solution to the following optimization problem

[0089]

[0090] When the number of base station antennas is large enough, the beam domain precoder All elements outside the non-zero beam set of user u are 0. Based on the above conclusion, assume that the spatial domain precoder has a beam structure p. u =VN u w u Then p u The design problem is transformed into a w u The design is asymptotically optimal. (Note:) Substituting into (13), we get

[0091]

[0092] in To extract statistical channel information with non-zero elements, the beam-domain precoder problem with the average signal-to-leakage-to-noise ratio maximization criterion can be written as follows:

[0093]

[0094] The design of a beam domain precoder for skywave massive MIMO based on the criterion of maximizing average signal-to-leakage-noise ratio includes the following steps:

[0095] Step 1: Calculation And perform Cholesky decomposition

[0096] Step 2: Calculation

[0097] Step 3: Calculation

[0098] Step 4: Calculation And perform eigenvalue decomposition

[0099] Step 5: Calculate the beam domain precoder for user u in To make w u Scaling factor that satisfies power constraints.

[0100] The precoding process for skywave massive MIMO beamstructure based on the average signal-to-leakage-to-noise ratio maximization criterion is as follows:

[0101] Calculate the precoding result of the transmitted symbol IV. Precoding Method for Skywave Large-Scale MIMO Beam Structure Based on Instantaneous Signal-to-Noise Ratio

[0102] Assuming the base station acquires perfect instantaneous channel information, and we focus on the downlink transmission precoding problem of the k-th subcarrier of the n-th OFDM symbol. For simplicity, the subscripts n and k are omitted below. The received signal model is as shown in equation (10).

[0103] The instantaneous signal-to-leakage-to-noise ratio (SNR) of user u is defined as the ratio of the signal energy intended to be transmitted to the signal energy and noise energy leaked to other users. Therefore, the expression for the instantaneous SNR of user u is:

[0104]

[0105] This leads to the problem of maximizing the instantaneous signal-to-noise ratio in precoding.

[0106]

[0107] Assume the pre-encoder has a beam structure p u =VN u w u Equation (18) can then be rewritten as follows:

[0108]

[0109] in Let be the extracted beam domain channel vector. According to the instantaneous signal-to-noise ratio maximization criterion, optimization problem (19) can be rewritten as:

[0110]

[0111] This problem is the generalized Rayleigh quotient problem, and its optimal solution satisfies

[0112]

[0113] Where max.eigenvector(A) represents the eigenvector corresponding to the largest eigenvalue of matrix A.

[0114] The design of a skywave massive MIMO beam domain precoder based on the instantaneous signal-to-noise ratio maximization criterion includes the following steps:

[0115] Step 1: Calculation

[0116] Step 2: Calculation Where γ is the value that makes w u A power scaling factor that satisfies power constraints.

[0117] The precoding process for skywave large-scale MIMO beamstructure based on the instantaneous signal-to-leakage-to-noise ratio maximization criterion is as follows:

[0118] Calculate the precoding result of the transmitted symbol

[0119] V. Implementation Results

[0120] To enable those skilled in the art to better understand the present invention, the performance results of the precoding method in this embodiment under a specific configuration are given below.

[0121] Considering a skywave massive MIMO-OFDM communication system, the system parameters are configured as follows: carrier frequency f c =16MHz, subcarrier spacing Δf=250Hz, number of subcarriers N c =2048, number of effective subcarriers N v =1536, base station antenna spacing d=9m, number of beams For ease of description, the skywave massive MIMO precoder based on maximizing the average signal-to-leakage-to-noise ratio is denoted as the ASLNR precoder, and the skywave massive MIMO beam domain precoder based on maximizing the average signal-to-leakage-to-noise ratio is denoted as the BS-ASLNR precoder; the skywave massive MIMO precoder based on maximizing the instantaneous signal-to-leakage-to-noise ratio is denoted as the SLNR precoder, and the skywave massive MIMO beam domain precoder based on maximizing the instantaneous signal-to-leakage-to-noise ratio is denoted as the BS-SLNR precoder.

[0122] First, we present the ASLNR precoder in embodiments with different numbers of base station antennas, and compare the sum and rate performance of the BS-ASLNR precoder at different total transmit powers. The number of users is set to U = 64. Figure 3Performance curves of the sum rate of the ASLNR precoder and the BS-ASLNR precoder under different total transmit powers and with varying numbers of base station antennas were plotted. The graphs show that the sum rate performance of both precoding methods improves with increasing antenna count, and the performance difference between the BS-ASLNR and ASLNR precoders is very small, remaining largely unchanged with the number of base station antennas. This indicates that the proposed BS-ASLNR precoder possesses excellent robustness.

[0123] Next, the SLNR precoder in embodiments with different numbers of base station antennas is presented, and the sum rate performance of the BS-SLNR precoder at different total transmit powers is compared. The number of users is set to U = 64. Figure 4 Performance curves of the sum rate of the SLNR and BS-SLNR precoders under different total transmit powers and with varying numbers of base station antennas were plotted. The graphs show that the sum rate performance of both precoding schemes improves with increasing antenna count, and the performance gap between the BS-SLNR and SLNR precoders narrows. This is because as the number of base station antennas increases, the channel vectors of different users become nearly orthogonal, reducing inter-user interference and thus minimizing the performance loss of the beamforming method. This performance gap disappears when the number of base station antennas approaches infinity.

[0124] Finally, a comparison of the design complexity of each precoder is presented. For the BS-ASLNR precoder and the ASLNR precoder, the required number of complex multiplications is used as the metric. The overall design complexity of the ASLNR precoder is... For BS-ASLNR pre-encoder design and C u The computational complexity is For C u The computational complexity of performing Cholesky decomposition and inverting the lower triangular matrix is ​​O(n). A′ u The computational and EVD decomposition complexity is... The computational complexity of the precoder is B. 2 U, therefore the overall design complexity of the BS-ASLNR precoder is Compared to the ASLNR maximization precoder design, where B << M when the number of base station antennas is large, the BS-ASLNR precoder has a significant advantage in terms of low complexity. For both the BS-SLNR and SLNR precoders, it is assumed that the noise power at each user location and the power constraint on the precoder are equal, i.e. P1 = ... = P U =P TIt can be proven that the SLNR precoder is equivalent to the MMSE precoder; therefore, its design complexity is the same as that of the MMSE precoder. The overall design complexity of the BS-SLNR preencoder is When the number of base station antennas and users is large, the beam domain channels are relatively sparse, usually with only a small number of non-zero beams. In this case, the design complexity of the BS-SLNR precoder is lower than that of the SLNR precoder.

[0125] This invention also discloses a computer system, including a memory, a processor, and a computer program / instructions stored in the memory and executable on the processor. When the computer program / instructions are executed by the processor, they implement the steps of a skywave massive MIMO beamstructure precoding method based on the average signal-to-noise ratio maximization criterion, or implement the steps of a skywave massive MIMO beamstructure precoding method based on the instantaneous signal-to-noise ratio maximization criterion.

[0126] This invention also discloses a computer program product, including a computer program / instruction, which, when executed by a processor, implements the steps of the skywave massive MIMO beamstructure precoding method based on the average signal-to-noise ratio maximization criterion, or implements the steps of the skywave massive MIMO beamstructure precoding method based on the instantaneous signal-to-noise ratio maximization criterion.

[0127] It is understood that the present invention has been described through some embodiments, and those skilled in the art will recognize that various changes or equivalent substitutions can be made to these features and embodiments without departing from the spirit and scope of the invention. Furthermore, under the teachings of the present invention, these features and embodiments can be modified to adapt to specific situations and materials without departing from the spirit and scope of the invention. Therefore, the present invention is not limited to the specific embodiments disclosed herein, and all embodiments falling within the scope of the claims of this application are within the protection scope of the present invention.

Claims

1. A precoding method for skywave massive MIMO beamstructure based on the criterion of maximizing average signal-to-leakage-to-noise ratio, characterized in that, include: Through beam matrix This achieves the transformation between spatial domain and beam domain channels, utilizing the sparsity of the downlink channel in the beam domain of skywave massive MIMO to transform the user... The non-zero beam index is denoted as the set. And using the space beam selection matrix Statistical channel information in the beam domain Extraction is performed to obtain the reduced-dimensional beam domain statistical channel information for each user. ;in Indicates the number of beam sampling points. Indicates user Number of non-zero beams occupied Represents a set Elements from smallest to largest express The first dimension of the identity matrix List; By utilizing reduced-dimensional beam domain statistical channel information, an optimization problem maximizing the average signal-to-noise ratio is formed, and the beam domain precoder for each user is obtained by solving the problem. ; Beam domain precoders for each user Send signals to users Multiplying these signals yields the precoded signals for each user's beam domain. Then, beam mapping is performed, and the summation of the precoded signals for each user's beam domain after beam mapping is obtained. ;in Indicates the number of users; Multiplying the beam matrix by the summation result yields... This enables the precoding of user signals; The average signal-to-noise ratio maximization optimization problem is formulated as follows: ； In the formula, For users Beam domain precoder, , For power constraints, For users The noise power, where the superscript H denotes the conjugate transpose of a matrix or vector. Represented by vector A diagonal matrix with diagonal elements; The steps for solving the optimization problem include: calculate And perform Cholesky decomposition ; calculate ; calculate ; calculate And perform eigenvalue decomposition ; Calculate users Beam domain pre-encoder in In order to make Scaling factor that satisfies power constraints; where express The first column of the 1-dimensional identity matrix.

2. The skywave massive MIMO beam structure precoding method based on the average signal-to-leakage-to-noise ratio maximization criterion as described in claim 1, characterized in that, The beam matrix A matrix consisting of a set of rudder vectors after uniformly sampling the direction cosines; beam domain statistical channel information. For users The beam domain channel coupling vector.

3. The skywave massive MIMO beam structure precoding method based on the average signal-to-leakage-to-noise ratio maximization criterion as described in claim 1, characterized in that, The user Occupied beam index set For users The set of beam position indices of the non-zero elements of the beam-domain channel; the reduced-dimensional beam-domain statistical channel information. For users Beam domain statistical channel information Using space beam selection matrix The vector formed by the extracted non-zero beam set position elements; the beam mapping is performed using a spatial beam selection matrix. The precoded signals of each user's beam domain are mapped to the positions occupied by the non-zero beams of that user in all beam indices according to the non-zero beam index.

4. A precoding method for skywave massive MIMO beamstructure based on the instantaneous signal-to-leakage-to-noise ratio maximization criterion, characterized in that, include: Through beam matrix To achieve the transformation between the spatial domain and the beam domain, the sparsity of the downlink channel in the beam domain of skywave massive MIMO is utilized to transform the user... The non-zero beam index is denoted as the set. And using the space beam selection matrix For beam domain channel vector Extraction is performed to obtain the reduced-dimensional beam domain channel vector for each user. ;in Indicates the number of beam sampling points. user Number of non-zero beams occupied Represents a set Elements from smallest to largest express The first dimension of the identity matrix List; Using reduced-dimensional beam domain channel vectors The problem of maximizing the signal-to-leakage-to-noise ratio using instantaneous channel information is formulated, and the beam domain precoder for each user is obtained by solving it. ; Beam domain precoders for each user Send signals to users Multiplying these signals yields the precoded signals for each user's beam domain, which are then used in conjunction with the spatial beam selection matrix. Beam mapping is performed, and the precoded signals of each user's beam domain after beam mapping are summed to obtain... ;in Indicates the number of users; Multiplying the beam matrix by the summation result yields... This enables the precoding of user signals; The problem of maximizing the signal-to-leakage-to-noise ratio using instantaneous channel information is described as follows: ； In the formula, For users Beam domain precoder, , For power constraints, For users The noise power, where the superscript H indicates the conjugate transpose of a matrix or vector; The steps for solving the optimization problem include: calculate ; calculate ,in In order to make A power scaling factor that satisfies power constraints.

5. The skywave massive MIMO beam structure precoding method based on the instantaneous signal-to-leakage-to-noise ratio maximization criterion as described in claim 4, characterized in that, The beam matrix The matrix is ​​a set of rudder vectors uniformly sampled from the direction cosines; the beam domain channel vector Let be a random vector whose elements are independent and non-identically distributed, and whose elements are the i-th elements. The OFDM symbol of the first Subcarrier users Beam domain channel coefficients at each beam position.

6. The skywave massive MIMO beam structure precoding method based on the instantaneous signal-to-leakage-to-noise ratio maximization criterion as described in claim 4, characterized in that, The user Occupied beam index set For users The set of beam position indices containing the non-zero elements of the beam-domain channel; the reduced-dimensional beam-domain channel vector. For users Beam domain channel vector Using space beam selection matrix Extract the vector formed by the non-zero beam set position elements; the beam mapping is performed using a spatial beam selection matrix. The precoded signals of each user's beam domain are mapped to the positions occupied by the non-zero beams of that user in all beam indices according to the non-zero beam index.

7. A computer system comprising a memory, a processor, and computer programs / instructions stored in the memory and executable on the processor, characterized in that, When the computer program / instruction is executed by the processor, it implements the steps of the skywave massive MIMO beam structure precoding method based on the average signal-to-noise ratio maximization criterion as described in any one of claims 1-3, or implements the steps of the skywave massive MIMO beam structure precoding method based on the instantaneous signal-to-noise ratio maximization criterion as described in any one of claims 4-6.

8. A computer program product comprising a computer program / instructions, characterized in that, When the computer program / instruction is executed by the processor, it implements the steps of the skywave massive MIMO beam structure precoding method based on the average signal-to-noise ratio maximization criterion as described in any one of claims 1-3, or implements the steps of the skywave massive MIMO beam structure precoding method based on the instantaneous signal-to-noise ratio maximization criterion as described in any one of claims 4-6.

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