Channel acquisition method and system for reconfigurable MIMO communication system

Abstract

The invention discloses a channel acquisition method and system for a reconfigurable MIMO communication system, and belongs to the technical field of wireless communication, and the method comprises the steps: selecting any one directional diagram from all reconfigurable directional diagrams of a transmitting end, enabling all antennas of the transmitting end to use the selected directional diagram, and estimating a channel corresponding to the selected directional diagram; all reconfigurable antennas of a transmitting end are grouped according to the number of reconfigurable directional diagrams, so that different grouped antennas use different directional diagrams, antennas in the same group use the same directional diagram, and channels corresponding to each group of directional diagrams are estimated; and obtaining an estimated channel path and corresponding angle information based on the estimated channel, and extrapolating channel state information corresponding to all directional diagrams. According to the invention, after the partial channel state information of the directional diagrams is estimated through a small amount of pilot signals, the channel state information corresponding to all the directional diagrams is extrapolated by using the estimated partial channel state information, so that the pilot overhead is effectively reduced.

Description

Technical Field

[0001] The present invention belongs to the technical field of wireless communication, and particularly relates to a channel acquisition method and system for a reconfigurable MIMO communication system. Background Art

[0002] With the change and development of wireless communication technologies, the limited spectrum resources can no longer meet the increasing demand for communication rates, which poses a great challenge to the design of communication systems. Reconfigurable antennas can change their operating states, such as frequency, polarization direction, and radiation pattern, etc., to adapt to different wireless communication requirements, and are considered one of the potential development directions of next-generation communication technologies. Specifically, there are various ways to implement reconfigurable antennas, such as RF switches, varactor diodes, mechanical actuators, or tunable materials. The principle is to redistribute the current on the antenna surface, thereby generating reversible property modifications.

[0003] As a core technology in the physical layer of wireless communication, MIMO (Multiple Input Multiple Output) technology can effectively exploit the spatial domain resources of communication systems and greatly improve the spectrum utilization rate of communication systems. Compared with traditional MIMO communication systems, combining reconfigurable antennas with MIMO technology enables the antenna to dynamically select an antenna pattern that matches the transmission environment, bringing additional degrees of freedom to the communication system and further improving the transmission performance of the system.

[0004] However, when the antenna pattern changes, the corresponding channel state information also changes. To obtain accurate channel state information, it is necessary to transmit pilots for channel estimation. At this time, if traditional channel estimation methods are used, the pilot overhead required by the system increases exponentially with the increase in the number of antennas and the number of patterns that each reconfigurable antenna can reconstruct, posing a huge challenge to the application of reconfigurable large-scale MIMO communication systems.

[0005] Currently, relevant literature has studied how to obtain the channel state information of reconfigurable communication systems, that is, estimating the channel information corresponding to some patterns through a small number of pilots and using the correlation between different patterns for channel extrapolation. However, the existing methods require perfect channel state statistical information to be known in advance, which is unacceptable for actual systems. Summary of the Invention

[0006] The purpose of the present invention is to address the above problems in the existing technologies, and provide a channel acquisition method and system for a reconfigurable MIMO communication system. After estimating partial channel state information of the pattern through a small number of pilot signals, all channel state information corresponding to all patterns is extrapolated using the estimated partial channel state information, effectively reducing the pilot overhead.

[0007] To achieve the above object, the present invention has the following technical solutions:

[0008] In a first aspect, a channel acquisition method for a reconfigurable MIMO communication system is provided, including:

[0009] Select any one of all the reconfigurable patterns at the transmitter end, use all the antennas at the transmitter end with the selected pattern, and estimate the channel corresponding to the selected pattern;

[0010] Group all the reconfigurable antennas at the transmitter end according to the number of reconfigurable patterns, so that different grouped antennas use different patterns, and the antennas within the same group use the same pattern, and estimate the channels corresponding to each group of patterns;

[0011] Based on the channel corresponding to the selected pattern estimated and the channels corresponding to each group of patterns, obtain the estimated signal path and the corresponding angle information, and extrapolate the channel state information corresponding to all patterns.

[0012] As a preferred solution, the base station end of the reconfigurable MIMO communication system is equipped with M antennas, the number of antennas at the receiving end is N, and only the antennas at the transmitter end are reconfigurable antennas; in the channel model of a point-to-point MIMO communication system, the steering vector and are:

[0013]

[0014] In the formula, d is the spacing between antennas, c represents the speed of light, represents the departure elevation angle corresponding to the j-th path in the i-th cluster, represents the horizontal angle corresponding to the j-th path in the i-th cluster, represents the arrival elevation angle corresponding to the j-th path in the i-th cluster at the receiving end, represents the antenna gain corresponding to the j-th path in the i-th cluster when the k-th antenna at the transmitter end uses the p-th pattern; the channel corresponding to the p-th pattern is:

[0015]

[0016] In the formula, represents the steering vector at the transmitter end, and the expression is When there is only one path in each cluster and all the antennas at the transmitter end use the same pattern, the channel model formula is simplified to:

[0017]

[0018] In the formula, represents the matrix composed of steering vectors, represents the path gain of the channel, represents the gain of the p-th antenna pattern.

[0019] As a preferred solution, the minimum mean square error (MMSE) channel estimation method is respectively used to estimate the channels corresponding to the selected one pattern and the channels corresponding to each group of patterns. The expression of the minimum mean square error (MMSE) channel estimation method is as follows:

[0020] Y = HX + W

[0021] H es = Y(X H R H X + σ 2 NI M ) -1 X H R H

[0022] In the formula, H es represents the estimated channel coefficient, X represents the pilot signal sequence to be transmitted, and Y represents the received signal matrix;

[0023] Assume that the number of reconfigurable antenna patterns is P, and the k-th pattern is selected from the P patterns for channel estimation. represents the channel matrix estimated using the k-th pattern;

[0024] All the transmitting antennas are divided into P groups, and the number of antennas in each group is Antennas in the same group use the same pattern, and different patterns are used between different groups. Define as the channel matrix estimated by the p-th group of transmitting antennas.

[0025] As a preferred solution, the channel state information corresponding to all patterns is extrapolated according to the following expression:

[0026]

[0027] In the formula, H p is the ideal channel matrix corresponding to the p-th pattern, represents the extrapolated channel matrix corresponding to the p-th pattern, represents the elevation angle of the i-th path at the transmitting end, represents the arrival elevation angle of the i-th path at the receiving end, g represents the path gain of the channel, r p represents the antenna gain corresponding to the p-th pattern, set represents the number of reconfigurable antenna patterns, L represents the number of paths of the channel, A r represents the matrix composed of the steering vectors at the receiving end, A t represents the matrix composed of the steering vectors at the transmitting end, represents the corresponding steering vector after grouping the transmitting - end antennas, The expression of

[0028]

[0029] As a preferred solution, obtaining the estimated channel paths and the corresponding angle information based on the estimated channels corresponding to the selected one pattern and the channels corresponding to each group of patterns includes the following steps:

[0030] The channel matrix estimated according to the k - th pattern and the channel matrix estimated by the p - th group of transmitting - end antennas Perform singular value decomposition (SVD) on the estimated channel where, represents the magnitude of the singular value of the matrix, N represents the number of receiving - end antennas, M represents the number of transmitting - end receiving antennas. Assuming N < M, a threshold δ is introduced to judge the number of paths of the channel:

[0031]

[0032] When the number of paths of the channel is greater than or equal to the number of receiving antennas N, an orthogonal matching pursuit (OMP) decomposition - based method is introduced, and an iteration threshold related to noise is defined, and the expression is:

[0033]

[0034] In the formula, M is the number of transmitting - end antennas, N is the number of receiving - end antennas, P fa represents the probability of algorithm detection error; represents the variance magnitude of the noise; The channel model is written in vector form, and the expression is:

[0035]

[0036] In the formula, represents the steering vector at the receiving end, represents the steering vector at the transmitting end, L represents the number of paths of the channel, α i represents the channel path gain, represents the antenna gain corresponding to the p - th pattern, h p represents the vector form of the channel matrix corresponding to the p - th pattern; Define a dictionary matrix for the OMP algorithm, and the expression is as follows:

[0037]

[0038] where \(e = \{1, 2, \ldots, 180\}\) represents the set of all elevation angles, and \(e_i\) i represents the \(i\)-th element in the set, and \(D\) t is the matrix composed of the steering vectors of all transmitters, and \(D\) r is the matrix composed of the steering vectors of all receivers, and \(D\) all represents the combined matrix of all steering vectors of transmitters and receivers; using to represent in its vectorized description, the angles are selected in the dictionary matrix. For the \(i\)-th iteration, the appropriate angle combination is searched using projection, and the expression is as follows:

[0039]

[0040] where represents the residual signal that cannot be accurately represented by the selected steering vectors, represents the departure elevation angle of the transmitter estimated in the \(i\)-th iteration, represents the arrival elevation angle of the receiver selected in the \(i\)-th iteration, and \(d\) i represents the index of the selected steering vector combination in the matrix \(D\) all ; assuming the set represents the index set selected after \(i\) iterations, the expressions for the channel path gain and the residual signal are described as:

[0041]

[0042] Define a function to remove duplicate elements in the angle set , and the expression is as follows:

[0043]

[0044] When the energy of the residual signal is less than the noise threshold, the iteration terminates, and the expression is as follows:

[0045]

[0046] When the iteration stops satisfying the iteration condition, remove the duplicate elements in the angle set , that is At this time, the number of elements in the set is the preliminarily estimated number of channel paths If the preliminarily estimated number of paths is greater than the number \(N\) of receiver antennas, refine the estimated number of channel paths again; Denotes the vector after normalizing the estimated channel path gain, and the expression is as follows:

[0047]

[0048] Wherein, Denotes the i-th element within the estimated path gain, Denotes the set The i-th element within; using Denotes the number of paths of the refined channel, η 1 Denotes a threshold close to 1, and the refining process is as follows:

[0049]

[0050] After the first refinement, if the data Is still greater than the receiving antenna N, then the second refinement is performed; using Denotes the ratio of the energy of each path to the energy of the i-th path, and the expression is as follows:

[0051]

[0052] Introduce a threshold η again 2 , when the element Is less than η 2 , then the corresponding path is discarded, and the angle corresponding to this path is discarded by the angle set , and the process of discarding the path is as follows:

[0053]

[0054] Wherein, Is the finally estimated number of channel paths.

[0055] As a preferred solution, for the channel matrix estimated for the k-th pattern And the channel matrix estimated by the p-th group of transmitting antennas Introduce a transformation matrix B for the k-th reconstructed pattern k , and extrapolate the channel state information corresponding to all patterns, and the expression is as follows:

[0056]

[0057] The expression of the transformation matrix corresponding to the p-th pattern is:

[0058]

[0059] The relationship between the transformation matrices of two different patterns is:

[0060] B p = B k ·R p,k

[0061] When the matrix R is obtained p,k the channel extrapolation expression of the p-th pattern is as follows:

[0062]

[0063] As a preferred solution, the matrix R p,k is solved by the following expression:

[0064]

[0065] s.t. R p,k = diag(r p,k ),

[0066]

[0067] wherein represents the steering vector matrix obtained using the estimated angle information, and L represents the number of estimated channel paths.

[0068] Second, a channel acquisition system for a reconfigurable MIMO communication system is provided, including:

[0069] A first-stage channel estimation module, configured to select an arbitrary pattern from all the reconfigurable patterns at the transmitter, use all the antennas at the transmitter with the selected pattern, and estimate the channel corresponding to the selected pattern;

[0070] A second-stage channel estimation module, which groups all the reconfigurable antennas at the transmitter according to the number of reconfigurable patterns, so that different grouped antennas use different patterns, and the antennas within the same group use the same pattern, and estimates the channels corresponding to each group of patterns;

[0071] A channel extrapolation module, configured to obtain the estimated channel paths and corresponding angle information based on the channel corresponding to the selected pattern estimated and the channels corresponding to each group of patterns, and extrapolate the channel state information corresponding to all patterns.

[0072] Third, an electronic device is provided, including:

[0073] A memory that stores at least one instruction; and a processor that executes the instruction stored in the memory to implement the channel acquisition method for the reconfigurable MIMO communication system.

[0074] Fourthly, a computer-readable storage medium is provided, characterized in that: at least one instruction is stored in the computer-readable storage medium, and the at least one instruction is executed by a processor in an electronic device to implement the channel acquisition method for a reconfigurable MIMO communication system.

[0075] Compared with the prior art, the present invention has at least the following beneficial effects:

[0076] For a reconfigurable large-scale MIMO communication system, the present invention proposes a low-overhead channel acquisition method and a two-stage antenna grouping channel estimation protocol. In the first stage, all antennas at the transmitter use the same pattern and perform channel estimation using traditional channel estimation methods. In the second stage, all antennas at the transmitter are grouped, antennas in different groups use different antenna patterns, and antennas in the same group use the same pattern to perform channel estimation again. After estimating the partial channel state information corresponding to all patterns, based on the proposed channel estimation protocol, the method of the present invention constructs an optimization problem for channel extrapolation. By using the estimated partial channel state information, the present invention can estimate the number of signal path and the corresponding angles of the channel, and extrapolate all the channel state information corresponding to different patterns. By using the channel extrapolation method of the present invention, in the scenario of a reconfigurable large-scale MIMO communication system, after estimating the partial channel state information of the pattern through a small number of pilot signals, all the channel state information corresponding to different patterns is extrapolated by using the estimated partial channel information, thus effectively reducing the pilot overhead of the system and promoting the application of reconfigurable antennas in practical communication systems. Description of the Drawings

[0077] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention, and those of ordinary skill in the art can obtain other related drawings without creative efforts based on these drawings.

[0078] Fig. 1(a) is a schematic diagram of a traditional channel estimation protocol.

[0079] Fig. 1(b) is a schematic diagram of the antenna grouping channel estimation protocol proposed in the embodiment of the present invention.

[0080] Figure 2 Fig. 21 is a schematic diagram of the channel extrapolation performance proposed in the embodiment of the present invention, where the number of patterns reconstructed by the reconfigurable antenna is P = 8, the number of antennas at the transmitter is M = 32, the number of antennas at the receiver is N = 8, and the number of signal paths of the channel is L = 10.

[0081] Figure 3Schematic diagram of the channel extrapolation performance proposed in the embodiments of the present invention, where the number of patterns reconstructed by the reconfigurable antenna is P = 8, the number of antennas at the transmitter is M = 64, the number of antennas at the receiver is N = 8, and the number of paths of the channel is L = 12. Detailed implementation manners

[0082] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, those of ordinary skill in the art can also obtain other embodiments without creative efforts.

[0083] Embodiment 1

[0084] The embodiments of the present invention propose a channel acquisition method for a reconfigurable MIMO communication system, including the following steps:

[0085] From all the reconfigurable patterns at the transmitter, select any one pattern, and use all the antennas at the transmitter with the selected pattern to estimate the channel corresponding to the selected pattern.

[0086] Group all the reconfigurable antennas at the transmitter according to the number of reconfigurable patterns, so that different groups of antennas use different patterns, and the antennas within the same group use the same pattern, and estimate the channels corresponding to each group of patterns.

[0087] Based on the channel corresponding to the selected pattern estimated and the channels corresponding to each group of patterns, obtain the estimated channel paths and the corresponding angle information, and extrapolate the channel state information corresponding to all patterns.

[0088] In a possible implementation manner, the method of the embodiments of the present invention is applicable to a base station side of a reconfigurable MIMO communication system equipped with M antennas, the number of antennas at the receiver is N, only the antennas at the transmitter are reconfigurable antennas, the antennas are uniform linear arrays, and the considered scenario is a point-to-point large-scale MIMO communication system. Specifically, considering the channel model of the reconfigurable large-scale MIMO communication system, the steering vector and can be expressed as:

[0089]

[0090] Among them, d is the spacing between antennas, c represents the speed of light, represents the elevation angle of departure corresponding to the jth path in the ith cluster, represents the horizontal angle corresponding to the jth path in the ith cluster, Denote the arrival elevation angle corresponding to the j-th path in the i-th cluster at the receiving end. Denote the antenna gain corresponding to the j-th path in the i-th cluster when the k-th antenna at the transmitting end uses the p-th pattern. When using the multipath channel model for description and assuming that all the reconfigurable antennas at the transmitting end use the same pattern, the channel corresponding to the p-th pattern can be obtained:

[0091]

[0092] Where, Denote the steering vector of the traditional transmitting end, which can be expressed as Furthermore, when assuming that there is only one path in each cluster and all the antennas at the transmitting end use the same pattern, the channel model formula can be simplified as:

[0093]

[0094] Where, Denote the matrix composed of steering vectors, Denote the path gain of the channel, Denote the gain of the p-th antenna pattern.

[0095] After determining the channel model, the embodiments of the present invention propose a two-stage low-overhead antenna grouping channel estimation protocol for channel extrapolation. Each stage adopts the traditional least mean square error (LMMSE) channel estimation method, which can be expressed as:

[0096] Y = HX + W

[0097] H es = Y(X H R H X + σ 2 NI M ) -1 X H R H

[0098] Where, H es Denote the estimated channel coefficients, X denotes the pilot signal sequence to be transmitted, and Y denotes the received signal matrix.

[0099] The traditional channel estimation protocol and the antenna grouping channel estimation protocol proposed by the present invention are shown in Fig. 1(a) and Fig. 1(b). Assume that each transmission frame consists of T transmission blocks. In each transmission block, a part of the transmitted symbols is used for channel estimation, and the rest is used for data transmission. Fig. 1(a) shows the traditional channel estimation protocol, using N CEA symbol is used to estimate the channel state information corresponding to all radiation patterns. In the antenna grouping channel estimation protocol proposed in the present invention, a two-stage channel estimation scheme is adopted. As shown in Fig. 1(b), the first N AP symbols are used to estimate the channel state information of each transmission block. In the first stage, an arbitrary radiation pattern is selected from P available antenna radiation patterns, and the linear minimum mean square error (LMMSE) method is used for channel estimation. In this stage, all antennas at the transmitter use the same radiation pattern, and it is defined as the estimated channel matrix. In the second stage, all reconfigurable antennas at the transmitter are divided into P groups, each group contains antennas. Antennas in the same group use a common radiation pattern, and antennas in different groups use different radiation patterns. The traditional channel estimation method is used for channel estimation, and it is defined as the channel matrix of the p-th group.

[0100] Based on the proposed channel estimation protocol, an optimization problem for channel extrapolation is constructed. Its feature is that after estimating part of the channel state information, all the channel state information of all radiation patterns is extrapolated by using the estimated part of the channel state information. The optimization problem corresponding to channel extrapolation can be constructed as:

[0101]

[0102] where H p is the channel matrix corresponding to the p-th radiation pattern, represents the extrapolated channel matrix corresponding to the p-th radiation pattern, represents the elevation angle of the i-th path at the transmitter, represents the arrival elevation angle of the i-th path at the receiver, g represents the path gain of the channel, r p represents the antenna gain corresponding to the p-th radiation pattern, the set represents the number of reconfigurable antenna radiation patterns, L represents the number of paths of the channel, represents the steering vector, which can be expressed as:

[0103]

[0104] Furthermore, only by solving the optimization problem can the goal of channel extrapolation be achieved. The optimization problem will be solved in two steps. First, the number of paths of the channel and the corresponding departure angles are estimated, and then all the channels corresponding to all radiation patterns are extrapolated by using the estimated information.

[0105] First, the number of paths of the channel is determined by an algorithm. Specifically, by using the proposed channel estimation protocol, the estimated channel matrices and After that, perform singular value decomposition (SVD) on the estimated channel. Among them, represents the magnitude of the singular value of the matrix, N represents the number of receiving antennas, M represents the number of transmitting antennas, and the considered scenario is a large-scale MIMO communication scenario. Therefore, it is assumed that N < M. By introducing a threshold δ, the number of paths of the channel can be judged, which can be specifically expressed as:

[0106]

[0107] It should be noted that due to the special properties of SVD, when the number of paths of the channel is greater than or equal to the number of receiving antennas N, the estimation method of the number of paths of the channel based on SVD is no longer applicable. An estimation method of the number of paths of the channel based on orthogonal matching pursuit (OMP) decomposition is introduced. First, define an iterative threshold related to noise.

[0108]

[0109] Among them, M is the number of transmitting antennas, N is the number of receiving antennas, and P fa represents the probability of algorithm detection error, represents the variance magnitude of the noise. In order to be able to use the OMP algorithm, the channel of the point-to-point MIMO communication system is written in vector form, which can be expressed as:

[0110]

[0111] Among them, represents the steering vector of the receiving end, represents the steering vector of the transmitting end, L represents the number of paths of the channel, and α i represents the path gain of the channel, represents the antenna gain corresponding to the p-th pattern, and h p represents the vector form of the channel matrix corresponding to the p-th pattern.

[0112] Based on the above channel model, define a dictionary matrix for the OMP algorithm as follows:

[0113]

[0114] Among them, e = {1, 2,..., 180} represents the set of all elevation angles, and e i represents the i-th element in the set, and D t is a matrix composed of all the steering vectors of the transmitting end, and D r is a matrix composed of all the steering vectors of the receiving end, and D all represents the combined matrix of all the steering vectors of the transmitting end and the receiving end. Use Representation The vectorized description of involves selecting angles in a dictionary matrix. For the i-th iteration, appropriate angle combinations are searched using projection, and the expression is as follows:

[0115]

[0116] Where, represents the residual signal that cannot be accurately represented by the selected steering vectors, represents the departure elevation angle of the transmitter estimated in the i-th iteration, represents the arrival elevation angle of the receiver selected in the i-th iteration, d i represents the index of the selected steering vector combination in matrix D all Assume the set represents the set of all indices selected in the iterations. After the i-th iteration, the path gain of the channel and the expression of the residual signal can be described as:

[0117]

[0118] To avoid repeatedly selecting the same angles, a function for removing duplicate elements in the angle set can be described as:

[0119]

[0120] Meanwhile, a termination condition for the loop is given, that is, when the energy of the residual signal is less than the noise threshold, the iteration terminates, and the expression is as follows:

[0121]

[0122] When the algorithm stops satisfying the iteration condition, remove the duplicate elements in the angle set That is At this time, the number of elements in the set is the number of signal paths of the channel initially estimated by the algorithm If the initially estimated number of paths is greater than the number of receiver antennas, the estimated number of signal paths will be refined again. represents the vector after normalizing the estimated path gain of the signal path and can be described as:

[0123]

[0124] Where, represents the i-th element in the estimated path gain, represents the i-th element in the set Use to represent the number of paths of the refined channel, η1 Denote a threshold close to 1, and the refinement process can be expressed as:

[0125]

[0126] After the first refinement, if the data is still greater than the receiving antenna N, the second refinement starts. Use to denote the ratio of the energy of each path to that of the i-th path, which can be described as:

[0127]

[0128] Meanwhile, introduce a threshold η 2 , when the element is less than η 2 , the corresponding path is discarded, and the angle corresponding to this path is also discarded by the angle set . The process of discarding paths can be described as:

[0129]

[0130] where is the finally estimated number of channel paths.

[0131] When the number of channel paths is estimated, the angle information corresponding to each path is also obtained. Using this information, channel extrapolation is performed. At this time, according to the estimated number of channel paths and angles, the matrix corresponding to the transmitter steering vector can be obtained. According to the proposed channel estimation protocol, the channel estimation matrix and Introduce a transformation matrix B for the k-th reconstructed pattern k , which can be described as:

[0132]

[0133] Similarly, the transformation matrix corresponding to the p-th pattern can be expressed as:

[0134]

[0135] The relationship between the transformation matrices of two different patterns can be expressed as:

[0136] B p = B k ·R p,k

[0137] Finally, when the matrix R p,k is obtained, channel extrapolation can be performed. The channel extrapolation formula for the p-th pattern is:

[0138]

[0139] Furthermore, matrix R p,k is crucial for channel extrapolation. By using optimization toolkits such as CVX to solve the optimization problem to obtain the final matrix, the optimization problem can be described as:

[0140]

[0141] s.t. R p,k = diag(r p,k ),

[0142]

[0143] where represents the steering vector matrix obtained using the estimated angle information, and L represents the estimated number of channel paths. When the matrix R p,k is solved, substituting it into the channel extrapolation formula, the channel matrix corresponding to each pattern is obtained.

[0144] Embodiment 2

[0145] The channel acquisition method of the embodiment of the present invention for a reconfigurable MIMO communication system includes the following steps:

[0146] S1. Select the k-th pattern from P patterns;

[0147] S2. The transmitting end transmits the pilot signal matrix X;

[0148] S3. Use the traditional channel estimation algorithm to estimate the channel

[0149] S4. Divide the transmitting end antennas into P groups, and each group of antennas uses a different pattern;

[0150] S5. The transmitting end transmits the pilot signal matrix X;

[0151] S6. Use the traditional channel estimation algorithm to estimate the channel

[0152] Furthermore, based on the proposed channel estimation protocol, estimate the number of channel paths and perform channel extrapolation, mainly including:

[0153] S101. Use the proposed channel estimation algorithm to perform channel estimation to obtain and

[0154] S102. Perform SVD decomposition on the matrix ;

[0155] S103. Estimate the number of signal path

[0156] S104. When At this time It is the estimated number of paths, otherwise, go to step S105;

[0157] S105. Initialize

[0158] S106. Calculate γ related to noise;

[0159] S107. Determine whether the condition If satisfied, enter the next step and start iteration;

[0160] S108. Calculate

[0161] S109. Update the set

[0162] S110. Update the set

[0163] S111. Obtain the signal path gain

[0164] S112. Update y re , determine whether the condition If satisfied, re-enter S108, if not, go to the next step;

[0165] S113. Remove duplicate elements and calculate

[0166] S114. If Calculate Otherwise Go to step S116;

[0167] S115. If Calculate Otherwise

[0168] S116. When the number of signal paths and the corresponding angles are estimated, solve for B k And use CVX to solve the optimization problem for R p,k of Substitute into the formula to extrapolate the channels corresponding to all radiation patterns:

[0169]

[0170] The channel acquisition method for a reconfigurable MIMO communication system according to the embodiments of the present invention is further described through the following simulation experiments:

[0171] Perform simulation tests in a time-varying channel environment.

[0172] The test conditions are as follows:

[0173] In a point-to-point reconfigurable massive MIMO communication system, the transmitter is equipped with M transmitting antennas, and the number of antennas at the receiver is N, assuming N << M. The pilot signal transmitted by the transmitter is an identity matrix.

[0174] The simulation results are as Figure 2 compared with Figure 3 shown. Among them, the simulation adds an algorithm for extrapolation using the correlation between radiation patterns in relevant literature. In addition, in addition to the low-overhead channel extrapolation scheme proposed in the present invention, the simulation also adds the results of channel estimation using traditional channel estimation algorithms as the baseline scheme of the present invention.

[0175] Please refer to Figure 2 compared with Figure 3 , and the channel extrapolation performance under different numbers of transmitting antennas and paths is respectively simulated. First, compared with existing channel extrapolation algorithms, the algorithm proposed in the present invention has better extrapolation performance and lower overhead. Compared with the most ideal LMMSE estimation algorithm, although the performance of the method of the present invention is lost, the required pilot overhead is smaller.

[0176] Another embodiment of the present invention also proposes a channel acquisition system for a reconfigurable MIMO communication system, including:

[0177] A first-stage channel estimation module, configured to select any one radiation pattern from all the reconfigurable radiation patterns at the transmitter, use all the antennas at the transmitter with the selected radiation pattern, and estimate the channel corresponding to the selected radiation pattern;

[0178] A second-stage channel estimation module, which groups all the reconfigurable antennas at the transmitter according to the number of reconfigurable radiation patterns, so that different grouped antennas use different radiation patterns, and the antennas within the same group use the same radiation pattern, and estimates the channels corresponding to each group of radiation patterns;

[0179] A channel extrapolation module, configured to obtain the estimated signal path and the corresponding angle information based on the channel corresponding to the selected radiation pattern and the channels corresponding to each group of radiation patterns estimated, and extrapolate the channel state information corresponding to all radiation patterns.

[0180] Another embodiment of the present invention also proposes an electronic device, including:

[0181] A memory that stores at least one instruction; and a processor that executes the instruction stored in the memory to implement the channel acquisition method for the reconfigurable MIMO communication system.

[0182] Another embodiment of the present invention further provides a computer-readable storage medium, in which at least one instruction is stored, and the at least one instruction is executed by a processor in an electronic device to implement the channel acquisition method for a reconfigurable MIMO communication system.

[0183] Exemplarily, the instructions stored in the memory can be divided into one or more modules / units, and the one or more modules / units are stored in the computer-readable storage medium and executed by the processor to complete the channel acquisition method for the reconfigurable MIMO communication system of the present invention. The one or more modules / units can be a series of computer-readable instruction segments capable of performing specific functions, and these instruction segments are used to describe the execution process of the computer program in the server.

[0184] The electronic device can be a computing device such as a smart phone, a notebook, a palm computer, and a cloud server. The electronic device may include, but is not limited to, a processor and a memory. Those skilled in the art can understand that the electronic device may further include more or fewer components, or combine certain components, or different components. For example, the electronic device may further include input / output devices, network access devices, a bus, etc.

[0185] The processor may be a Central Processing Unit (CPU), or may also be other general-purpose processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field-Programmable Gate Arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor, or the processor may also be any conventional processor, etc.

[0186] The memory may be an internal storage unit of the server, such as the hard disk or memory of the server. The memory may also be an external storage device of the server, such as a plug-in hard disk equipped on the server, a Smart Media Card (SMC), a Secure Digital (SD) card, a Flash Card, etc. Further, the memory may also include both the internal storage unit of the server and the external storage device. The memory is used to store the computer-readable instructions and other programs and data required by the server. The memory may also be used to temporarily store the data that has been output or will be output.

[0187] It should be noted that, for the content such as the information interaction and execution process between the above module units, since it is based on the same concept as the method embodiment, for its specific functions and the technical effects brought, reference may be specifically made to the method embodiment part, and details are not described herein again.

[0188] Those skilled in the art can clearly understand that, for the convenience and simplicity of description, only the above division of each functional unit and module is used as an example for illustration. In actual applications, the above functions can be allocated to different functional units and modules according to needs, that is, the internal structure of the device is divided into different functional units or modules to complete all or part of the functions described above. Each functional unit and module in the embodiment can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit. The above integrated unit can be implemented in the form of hardware or in the form of a software functional unit. In addition, the specific names of each functional unit and module are only for the convenience of mutual distinction and do not limit the protection scope of the present application. The specific working process of the units and modules in the above system can refer to the corresponding process in the foregoing method embodiment, and details are not described herein again.

[0189] When the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, to implement all or part of the processes in the above-described embodiment methods of the present application, a computer program can be used to instruct the relevant hardware to complete. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by a processor, the steps of the above-described various method embodiments can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in the form of source code, object code, executable file, or some intermediate form, etc. The computer-readable medium can at least include: any entity or device capable of carrying the computer program code to the photographing device / terminal device, recording medium, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal, and software distribution medium. For example, a USB flash drive, a mobile hard disk, a magnetic disk, or an optical disc, etc.

[0190] In the above embodiments, the descriptions of the various embodiments have their own emphases. For the parts not detailed or recorded in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0191] The above-described embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions recorded in the foregoing various embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the various embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. A channel acquisition method for a reconfigurable MIMO communication system, characterized in that: include: Select one directional pattern from all reconfigurable directional patterns of the transmitting end, use the selected directional pattern for all antennas of the transmitting end, and estimate the channel corresponding to the selected directional pattern; All reconfigurable antennas at the transmitting end are grouped according to the number of reconfigurable directional patterns, so that antennas in different groups use different directional patterns, and antennas in the same group use the same directional pattern, and the channels corresponding to the directional patterns of each group are estimated; Based on the estimated channel corresponding to the selected directional pattern and the channels corresponding to each group of directional patterns, the estimated channel path and the corresponding angle information are obtained, and the channel state information corresponding to all directional patterns is extrapolated.

2. The channel acquisition method for a reconfigurable MIMO communication system according to claim 1, characterized in that: The base station of the reconfigurable MIMO communication system is equipped with M antennas, the number of antennas at the receiving end is N, and only the antenna at the transmitting end is a reconfigurable antenna; in the channel model of the point-to-point MIMO communication system, the steering vector and for: In the formula, χ=2πdf / c, d is the distance between the antennas, c is the speed of light, represents the departure pitch angle corresponding to the jth path in the i-th cluster, represents the horizontal angle corresponding to the jth path in the i-th cluster, represents the arrival pitch angle corresponding to the jth path in the i-th cluster at the receiving end, It represents the antenna gain corresponding to the jth path in the ith cluster when the kth antenna of the transmitter uses the pth pattern; the channel corresponding to the pth pattern is: In the formula, represents the guiding vector of the transmitter, which is expressed as When there is only one path in each cluster and all antennas at the transmitting end use the same directivity pattern, the channel model formula is simplified to: In the formula, represents the matrix composed of steering vectors, represents the path gain of the channel, represents the gain of the pth antenna pattern.

3. The channel acquisition method for a reconfigurable MIMO communication system according to claim 1, characterized in that: The minimum mean square error LMMSE channel estimation method is used to estimate the channel corresponding to the selected directional pattern and the channels corresponding to each group of directional patterns. The expression of the minimum mean square error LMMSE channel estimation method is as follows: Y=HX+W H es =Y(X H R H X+σ 2 NI M ) -1 X H R H In the formula, H es represents the estimated channel coefficient, X represents the pilot signal sequence to be transmitted, and Y represents the received signal matrix; Assume that the number of antenna reconfigurable patterns is P, and select the kth pattern from the P patterns for channel estimation. represents the channel matrix estimated using the k-th pattern; Divide all transmitting antennas into P groups, and the number of antennas in each group is Antennas in the same group use the same directional pattern, and different groups use different directional patterns. represents the channel matrix estimated by the pth group of transmitting antennas.

4. The channel acquisition method for a reconfigurable MIMO communication system according to claim 3, characterized in that: The channel state information corresponding to all directional patterns can be extrapolated according to the following expression: In the formula, H p is the ideal channel matrix corresponding to the p-th pattern, represents the extrapolated channel matrix corresponding to the p-th pattern, represents the pitch angle of the i-th path at the transmitter, represents the arrival elevation angle of the i-th path at the receiving end, g represents the path gain of the channel, r p represents the antenna gain corresponding to the p-th pattern, the set represents the number of reconfigurable antenna patterns, L represents the number of channel paths, A r A represents the matrix composed of the steering vectors at the receiving end. t represents the matrix composed of the guiding vectors at the transmitter, represents the corresponding steering vector after the transmitting antennas are grouped, The expression is as follows:

5. The channel acquisition method for a reconfigurable MIMO communication system according to claim 4, characterized in that: The obtaining of the estimated channel path and the corresponding angle information based on the estimated channel corresponding to the selected directional pattern and the channels corresponding to each group of directional patterns comprises the following steps: The channel matrix estimated from the kth pattern The channel matrix estimated by the p-th group of transmitting antennas Perform singular value SVD decomposition on the estimated channel in, Represents the size of the singular value of the matrix, N represents the number of receiving antennas, M represents the number of transmitting receiving antennas, assuming N < M, a threshold δ is introduced to determine the number of channel paths: When the number of channel paths is greater than or equal to the number of receiving antennas N, a method based on orthogonal matching pursuit (OMP) decomposition is introduced to define an iterative threshold related to noise, expressed as: Where M is the number of transmitting antennas, N is the number of receiving antennas, and P fa Indicates the probability of the algorithm detecting an error; Represents the variance of the noise; the channel model is written in the form of a vector, and the expression is: In the formula, represents the steering vector at the receiving end, represents the guiding vector of the transmitter, L represents the number of channel paths, α i represents the channel path gain, represents the antenna gain corresponding to the pth pattern, h p Represents the vector form of the channel matrix corresponding to the p-th directional pattern; defines a dictionary matrix of the OMP algorithm, the expression is as follows: Where, e = {1, 2, ..., 180} represents the set of all pitch angles, e i represents the i-th element in the set, D t is a matrix composed of the steering vectors of all transmitters, D r is a matrix composed of the steering vectors of all receivers, D all Represents the combined matrix of all steering vectors at the transmitter and receiver; use express The vectorized description is used to select the angle in the dictionary matrix. For the i-th iteration, the projection is used to search for the appropriate angle combination. The expression is as follows: In the formula, represents the residual signal that cannot be accurately represented by the selected steering vector, represents the departure pitch angle of the transmitter estimated at the i-th iteration, represents the arrival pitch angle of the receiver selected in the i-th iteration, d i Indicates the selected steering vector combination in the matrix D all The index of ; assuming the collection The index set selected after i iterations, the path gain of the channel and the expression of the residual signal are described as: Define a set of removal angles The function of repeated elements is as follows: When the energy of the residual signal is less than the noise threshold, the iteration is terminated, and the expression is as follows: When the iteration condition is met, remove the angle set Repeating elements within At this time, the collection The number of inner elements is the number of channel paths estimated initially. If the number of paths initially estimated is greater than the number of antennas N at the receiving end, and the estimated number of channel paths is refined again; Represents the vector after normalization of the estimated channel path gain, and the expression is as follows: in, represents the i-th element in the estimated path gain, Representing a collection The i-th element in ; use represents the number of paths of the refined channel, η1 represents a threshold close to 1, and the refining process is as follows: After the first refinement, if the data If it is still greater than the receiving antenna N, a second refinement is performed; use It represents the ratio of the energy of each path to the energy of the i-th path, and the expression is as follows: A threshold η2 is introduced again, when the element When it is less than η2, the corresponding path is discarded, and the angle corresponding to this path is included in the angle set The process of discarding the path is as follows: in, is the final estimated number of channel paths.

6. The channel acquisition method for a reconfigurable MIMO communication system according to claim 5, characterized in that: The channel matrix estimated for the kth pattern is The channel matrix estimated by the p-th group of transmitting antennas Introduce a transformation matrix B for the kth reconstructed directional pattern k , extrapolate the channel state information corresponding to all directional patterns, and the expression is as follows: The transformation matrix expression corresponding to the pth directional pattern is: The relationship between the transformation matrices of two different directional patterns is: B p =B k ·R p,k When the matrix R is found p,k After that, the channel extrapolation expression of the pth directional pattern is:

7. The channel acquisition method for a reconfigurable MIMO communication system according to claim 6, characterized in that: The matrix R p,k Solve it by the following expression: s.t.R p,k =diag(r p,k ), r i p,k >0,i=1,2,…,L. In the formula, represents the steering vector matrix obtained using the estimated angle information, and L represents the estimated number of channel paths.

8. A channel acquisition system for a reconfigurable MIMO communication system, characterized in that: include: The first-stage channel estimation module is used to select one directional pattern from all reconfigurable directional patterns of the transmitting end, use the selected directional pattern for all antennas of the transmitting end, and estimate the channel corresponding to the selected directional pattern; The second-stage channel estimation module groups all the reconfigurable antennas at the transmitting end according to the number of reconfigurable directional patterns, so that antennas in different groups use different directional patterns, and antennas in the same group use the same directional pattern, and estimates the channels corresponding to the directional patterns of each group; The channel extrapolation module is used to obtain the estimated channel path and corresponding angle information based on the estimated channel corresponding to the selected directional pattern and the channels corresponding to each group of directional patterns, and to extrapolate the channel state information corresponding to all directional patterns.

9. An electronic device, characterized in that: include: A memory storing at least one instruction; and A processor executes instructions stored in the memory to implement the channel acquisition method for a reconfigurable MIMO communication system as claimed in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores at least one instruction, and the at least one instruction is executed by a processor in an electronic device to implement the channel acquisition method for a reconfigurable MIMO communication system as claimed in any one of claims 1 to 7.

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