Data transmission method and communication device based on over-the-air computation-based channel estimation

Abstract

The application provides a data transmission method based on over-the-air computation and channel estimation and a communication device, and relates to the technical field of communication. The method comprises the following steps: a first access network device of a first cell receives an uplink signal from a terminal in the first cell; the first access network device decodes the uplink signal by using a decoding matrix of the first access network device to obtain uplink data; the decoding matrix of the first access network device is calculated based on a first precoding matrix of multiple cells, a second precoding matrix of each terminal in the multiple cells, an equivalent channel matrix between each terminal in the multiple cells and the first access network device, a variance of channel noise superimposed in a channel between each terminal in the multiple cells and the first access network device, and a variance of channel estimation error between each terminal in the multiple cells and the first access network device. The multiple cells comprise the first cell. The method can improve the accuracy of terminal uplink data transmission under the premise of actual channel estimation.

Description

TECHNICAL FIELD

[0001] Embodiments of the present application relate to the technical field of communication, and in particular, to a data transmission method based on over-the-air computation and a communication device. BACKGROUND

[0002] In the next generation wireless network, terminals in a cell can integrate communication and computation when communicating with an access network device (such as an access point (AP)) by combining over-the-air computation. Over-the-air computation (AirComp) is an efficient data aggregation solution that can combine communication and computation to achieve efficient data aggregation and other functions by utilizing the superposition characteristics of a wireless channel.

[0003] Among them, in addition to the inherent characteristics such as fading and noise of the wireless channel, it will also be affected by interference from external signals, resulting in distortion of the signal in the transmission process. In the AirComp system, the sending end and the receiving end can use the precoding matrix and the decoding matrix to compensate for and overcome the above-mentioned fading, noise and interference. Specifically, the precoding matrix is used to preprocess the data (such as adjusting the amplitude and phase of the data) at the sending end (such as the terminal) to compensate for the fading of the channel and other effects, so that better signal superposition and calculation can be performed at the receiving end. The decoding matrix is used to suppress the interference of external signals according to the received signal and the known channel characteristics at the receiving end (such as the AP), separate the data of each sending end from the superimposed signal or directly obtain the expected calculation result, and overcome the effects of noise and interference. As can be seen, the generation of the precoding matrix and the decoding matrix depends on the channel state information possessed by the receiving end and the sending end, and the performance of the AirComp system can be optimized by designing appropriate precoding matrix and decoding matrix.

[0004] Further, in the AirComp system, interference from external signals also affects the accuracy of uplink data transmission from the sending end to the receiving end. Specifically, when the access network device in the cell receives uplink data from the terminals in the cell, it will also be affected by uplink interference data from terminals in other cells, thereby affecting the accuracy of the function calculation result (such as the sum of the uplink data) of the uplink data of the terminals in the cell received by the access network device in the cell.

[0005] However, in actual deployment, the sending end and the receiving end often cannot have accurate channel state information; only the estimated or measured channel state information can be mastered. Then, how to reduce the influence of wireless channel fading, noise and uplink interference data of other cells received by the access network equipment of each cell in the AirComp system composed of multiple cells based on the inaccurate channel state information obtained by estimation / measurement, so as to improve the accuracy of uplink data transmission of the terminals in each cell, is a problem to be solved. SUMMARY

[0006] Embodiments of the present application provide a data transmission method and a communication device based on channel estimation under air computation, for improving the accuracy of uplink data transmission of terminals in each cell in an AirComp system composed of multiple cells.

[0007] In a first aspect, a data transmission method based on channel estimation under air computation is provided, which is applied to a first access network device corresponding to a first cell. In the method, the first access network device can receive uplink signals from terminals in the first cell. Then, the first access network device can decode the uplink signals by using a decoding matrix of the first access network device to obtain uplink data. The decoding matrix is calculated based on a first precoding matrix of multiple cells, a second precoding matrix of each terminal in the multiple cells, an equivalent channel matrix between each terminal in the multiple cells and the first access network device, a variance of channel noise superimposed in a channel between each terminal in the multiple cells and the first access network device, and a variance of channel estimation error between each terminal in the multiple cells and the first access network device. That is, the calculation of the decoding matrix used by the first access network device not only refers to the precoding matrix (including the first precoding matrix and the second precoding matrix) of each terminal in the cell, but also refers to the precoding matrix of each terminal in other cells. Therefore, the first access network device uses such a decoding matrix can minimize the interference signals received by the first access network device from other cells except the first cell, minimize the influence of channel estimation error during signal transmission and channel noise during signal transmission, and thus improve the accuracy of uplink signal transmission of terminals in each cell.

[0008] Further, the first precoding matrix of one cell (e.g., the first cell) is used to align the uplink interference data received by the first access network device from other cells in the plurality of cells. The second precoding matrix of one terminal (e.g., the first terminal) in one cell (e.g., the first cell) is used to align the uplink data sent by each terminal in the first cell to the first access network device. That is, the precoding matrix used to calculate the decoding matrix is a double-layer precoding matrix, one layer of the precoding matrix (e.g., the first precoding matrix) is used for interference alignment of other cells, and the other layer of the precoding matrix (e.g., the second precoding matrix) is used for alignment of uplink signals in the cell. In this way, the accuracy of the first access network device receiving the target signal can be further improved, and the interference of other cells to the first access network device receiving the uplink signal can be reduced.

[0009] Further, the equivalent channel matrix is the product of the channel estimation matrix between each terminal in the plurality of cells and the first access network device and the corresponding second precoding matrix. The plurality of cells includes the first cell. The equivalent channel matrix refers to the channel estimation matrix between each terminal in the plurality of cells and the first access network device, and considers that the channel characteristics between different terminals and the first access network device are different, so that the equivalent channel matrix is more consistent with the channel characteristics in the actual signal transmission process.

[0010] In a possible implementation of the first aspect, the first precoding matrix of the first cell is different from the first precoding matrix of other cells. Since the terminals in different cells will interfere with each other, especially in the cell edge area. Therefore, by designing different first precoding matrices for terminals in different cells, the interference between cells can be coordinated, and the performance of the entire system can be improved. The second precoding matrix of the first terminal is different from the second precoding matrix of other terminals in the first cell, and the second precoding matrix of the first terminal is different from the second precoding matrix of terminals in other cells. That is, different terminals in the same cell use different second precoding matrices, and terminals in different cells use different second precoding matrices. By this method, the channel characteristics between different terminals and the same access network device can be considered to be different, so different second precoding matrices are designed according to the respective channel characteristics, which can enable the signal of each terminal to be correctly received and decoded at the access network device.

[0011] In a possible implementation of the first aspect, each terminal (e.g., the first terminal) in the plurality of cells and the access network device are respectively configured with M antennas, and the uplink data sent by each terminal (e.g., the first terminal) in the plurality of cells is multi-stream data, and the multi-stream data includes d data streams. That is, this scheme can be used for single-antenna or single-stream data transmission, or can be applied to multi-antenna or multi-stream data transmission.

[0012] And, according to the number of antennas M and the number of uplink data streams d, the precoding matrix of each terminal (such as the first terminal) of the plurality of cells is a Mxd matrix, the first precoding matrix of the plurality of cells (such as the first cell) is a Mxd matrix, and the second precoding matrix of each terminal (such as the first terminal of the first cell) of the plurality of cells is a MxM matrix.

[0013] In a possible implementation of the first aspect, before the first access network device decodes the uplink signal using the decoding matrix of the first access network device to obtain the uplink data, the first access network device can further receive the nth round precoding matrix of the terminal of the plurality of cells. For example, the first access network device receives the nth round precoding matrix of the first terminal, and the nth round precoding matrix of the first terminal includes the nth round first precoding matrix of the first cell and the second precoding matrix of the first terminal, and n is sequentially taken from the set {1, 2, 3, …, N-1}. The first round first precoding matrix of the first cell is a random matrix satisfying the quasi-unitary constraint, the conjugate transpose of the matrix satisfying the quasi-unitary constraint multiplied by the matrix satisfying the quasi-unitary constraint is equal to the unit matrix, and the matrix satisfying the quasi-unitary constraint is a Mxd matrix. The column vectors of the first round first precoding matrix of the first cell satisfying the quasi-unitary constraint are orthogonal, so that the uplink data transmitted by the terminal of the first cell is encoded using the first round first precoding matrix of the first cell, the obtained uplink signal can maintain good orthogonality during transmission, thereby reducing the interference of other cells on the uplink transmission of the terminal signal of the cell. The second precoding matrix of the first terminal is the inverse matrix of the channel estimation matrix between the first terminal and the first access network device. In this way, when the channel condition changes (such as user movement, environmental change, etc.), the channel estimation matrix will be updated, and the second precoding matrix of the first terminal will also be adjusted accordingly, so that this adjustment can dynamically adapt to the channel change and maintain the stability of the uplink signal transmission.

[0014] Then, the first access network device can calculate the n th round decoding matrix of the first cell based on the n th round first precoding matrix of the plurality of cells, the second precoding matrix of each terminal in the plurality of cells, the equivalent channel matrix between each terminal in the plurality of cells and the first access network device, the variance of the channel noise superimposed in the channel between each terminal in the plurality of cells and the first access network device, and the variance of the channel estimation error between each terminal in the plurality of cells and the first access network device. That is, the calculation of the n th round decoding matrix of the first cell not only refers to the n th round first precoding matrix of each terminal in the first cell, but also refers to the n th round first precoding matrix of each terminal in the other cells and the second precoding matrix of each terminal in the plurality of cells. Therefore, the n th round decoding matrix of the first access network device calculated through multiple rounds can gradually correct the error of the decoding matrix obtained in the last round, so that the decoding result is closer to the target received signal, and the interference signal can be better suppressed to improve the accuracy of decoding. Moreover, the equivalent channel matrix is the product of the channel estimation matrix between each terminal in the plurality of cells and the first access network device and the corresponding second precoding matrix, and the plurality of cells include the first cell and the other cells.

[0015] In this implementation, the first access network device can perform N rounds of interaction with the first terminal, calculate the N th round decoding matrix of the first access network device as the decoding matrix of the first access network device. Through N rounds of interaction, the first access network device can continuously adjust the decoding matrix according to the optimization result of the precoding matrix, so as to more accurately decode the received signal and improve the accuracy of decoding.

[0016] In a possible implementation of the first aspect, after the first access network device calculates the n th round decoding matrix of the first cell, the first access network device can further send the n th round decoding matrix of the first cell to the first terminal. The n th round decoding matrix of the first cell is used by the first terminal to calculate the n+1 th round first precoding matrix of the first cell, and the n+1 th round precoding matrix of the first terminal includes the n+1 th round first precoding matrix of the first cell and the second precoding matrix of the first terminal. That is, the calculation of the n+1 th round first precoding matrix of the first cell refers to the n th round decoding matrix of the first cell, which can gradually correct the error of the first precoding matrix obtained in the last round, so that the first precoding matrix is better used for alignment of interference from other cells.

[0017] In a possible implementation of the first aspect, after the first access network device calculates the n-th decoding matrix of the first cell, the first access network device can further receive the N-th precoding matrix of the terminal from the plurality of cells. The N-th precoding matrix of the first terminal includes the N-th first precoding matrix of the first cell and the second precoding matrix of the first terminal. Then, the first access network device can calculate the N-th decoding matrix of the first cell based on the N-th first precoding matrix of the plurality of cells, the second precoding matrix of each terminal in the plurality of cells, the equivalent channel matrix between each terminal in the plurality of cells and the first access network device, the variance of the channel noise superimposed in the channel between each terminal in the plurality of cells and the first access network device, and the variance of the channel estimation error between each terminal in the plurality of cells and the first access network device. That is, after N rounds of interaction iteration, the first access network device can calculate the finally obtained N-th decoding matrix of the first cell. The first access network device uses the N-th decoding matrix of the first cell to decode the received uplink signal, can suppress the interference signal while better receiving the target signal, and improves the decoding accuracy.

[0018] In a possible implementation of the first aspect, the first access network device calculates the n-th decoding matrix of the first cell based on the n-th first precoding matrix of the plurality of cells, the second precoding matrix of each terminal in the plurality of cells, the equivalent channel matrix between each terminal in the plurality of cells and the first access network device, the variance of the channel noise superimposed in the channel between each terminal in the plurality of cells and the first access network device, and the variance of the channel estimation error between each terminal in the plurality of cells and the first access network device, including:

[0019] ;

[0020] wherein, denotes the equivalent channel matrix between the k-th terminal in the j-th cell and the access network device of the i-th cell, denotes the n-th first precoding matrix of the j-th cell, denotes the conjugate transpose of the n-th first precoding matrix of the j-th cell, denotes the conjugate transpose of the equivalent channel matrix between the k-th terminal in the j-th cell and the access network device of the i-th cell, denotes the variance of the channel estimation error between the k-th terminal in the j-th cell and the access network device of the i-th cell, denotes the trace of the matrix in the parentheses, denotes the second precoding matrix of the k-th terminal in the j-th cell, denotes the conjugate matrix of the second precoding matrix of the k-th terminal in the j-th cell, denotes the variance of the additive white Gaussian noise vector superimposed in the channel, denotes a unit matrix, denotes an equivalent channel matrix between the kth terminal in the ith cell and the access network device in the ith cell, denotes the nth round of the first precoding matrix of the ith cell, i, j = 1, …, Ku, k = 1, …, Ka, there are Ku cells in total, and each cell has Ka terminals. The iterative formula can gradually correct the error of the decoding matrix by updating the nth round decoding matrix of the first cell multiple times, so as to obtain a more suitable decoding matrix.

[0021] In a possible implementation of the first aspect, the first round of the first precoding matrix of the first cell is a randomly generated Mxd matrix satisfying the quasi-unitary constraint. That is, the first round of the first precoding matrix of the first cell (a matrix satisfying the quasi-unitary constraint) is randomly generated. Compared with a deterministic matrix, using a random matrix satisfying the quasi-unitary constraint can avoid falling into a local optimum due to the fixed pattern of the initial precoding matrix, and the randomly generated matrix satisfying the quasi-unitary constraint can provide a richer search space for subsequent iterations (such as gradient descent and alternating optimization), thereby accelerating the convergence.

[0022] Based on the method provided in the present application, the decoding matrix finally obtained through interactive iteration can minimize the sum of the mean square errors of the uplink data actually received by the first access network device and the target uplink data. The method provided in the present application can not only be applied to an air computing system of two cells, but also be applied to an air computing system of three or more cells.

[0023] In a second aspect, a data transmission method based on air computing channel estimation is provided, which is applied to a first terminal, and the first terminal is a terminal of a first cell. In the method, the first terminal can obtain a precoding matrix of the first terminal. Then, the first terminal encodes uplink data by using the precoding matrix of the first terminal to obtain an uplink signal, and the first terminal sends the uplink signal to a first access network device.

[0024] As described in the first aspect, the precoding matrix of the first terminal is a double-layer precoding matrix. One layer of the precoding matrix (such as the first precoding matrix) is used for interference alignment of other cells, and the other layer of the precoding matrix (such as the second precoding matrix) is used for interference alignment of the cell. In this way, the accuracy of the first access network device receiving the target signal can be improved, and the interference of other cells to the first access network device receiving the uplink signal can be reduced.

[0025] In a possible implementation of the second aspect, the first precoding matrix of the first cell is calculated based on the decoding matrices of the plurality of cells, the second precoding matrices of the terminals in the first cell, the equivalent channel matrices between the terminals in the first cell and the access network devices of the plurality of cells, the variance of the channel estimation errors between the terminals in the plurality of cells and the first access network device, and a plurality of Lagrange multipliers. That is, the calculation of the first precoding matrix used by the first cell not only refers to the decoding matrix of the current cell, but also refers to the decoding matrices of other cells. Therefore, the first cell adopts such a first precoding matrix to align the uplink interference signals of other cells, so as to facilitate the first access network device to better suppress the interference signals.

[0026] In a possible implementation of the second aspect, the first terminal can calculate the precoding matrix of the first terminal, and the method comprises: the first terminal calculates the nth round precoding matrix of the first terminal, and sends the nth round precoding matrix of the first terminal to the first access network device. Wherein, the nth round precoding matrix of the first terminal comprises the nth round first precoding matrix of the first cell and the second precoding matrix of the first terminal, and n is sequentially taken from the set {1, 2, 3, …, N-1}. The first round first precoding matrix of the first cell is a random matrix satisfying the quasi-unitary constraint, the conjugate transpose of the matrix satisfying the quasi-unitary constraint multiplied by the matrix satisfying the quasi-unitary constraint equals the unit matrix, and the matrix satisfying the quasi-unitary constraint is an Mxd matrix. The second precoding matrix of the first terminal is the inverse matrix of the channel estimation matrix between the first terminal and the first access network device.

[0027] Then, the first terminal receives the nth round decoding matrix of the first cell from the first access network device. Wherein, the nth round decoding matrix of the first cell is calculated based on the nth round first precoding matrix of the plurality of cells, the second precoding matrices of the terminals in the plurality of cells, the equivalent channel matrices between the terminals in the plurality of cells and the first access network device, the variance of the channel noise superimposed in the channel between the terminals in the plurality of cells and the first access network device, and the variance of the channel estimation errors between the terminals in the plurality of cells and the first access network device. The equivalent channel matrix is the product of the channel estimation matrix between the terminals in the plurality of cells and the first access network device and the corresponding second precoding matrix.

[0028] After the first terminal receives the n th round decoding matrix of the first cell from the first access network device, the first terminal can calculate the n+1 th round first precoding matrix of the first cell based on the n th round decoding matrix of the plurality of cells, the second precoding matrix of each terminal in the first cell, the equivalent channel matrix between each terminal in the first cell and the access network device of the plurality of cells and the variance of the channel estimation error between each terminal in the plurality of cells and the first access network device, and the plurality of Lagrange multipliers. The n+1 th round precoding matrix of the first terminal includes the n+1 th round first precoding matrix of the first cell and the second precoding matrix of the first terminal.

[0029] In this implementation, the first terminal can perform N rounds of interaction with the first access network device to calculate the N th round precoding matrix (double-layer precoding matrix) of the first terminal as the precoding matrix of the first terminal. Through the N rounds of interaction, the first terminal can continuously adjust the precoding matrix according to the optimization result of the decoding matrix to maximize the signal transmission performance of the system, thereby better adapting to complex channel state information, suppressing uplink transmission interference, and thereby enhancing the signal transmission quality.

[0030] In a possible implementation of the second aspect, the first terminal can obtain a plurality of Lagrange multipliers. The plurality of Lagrange multipliers correspond to the plurality of cells one by one, the plurality of cells include the first cell and other cells, and the Lagrange multiplier is a Lagrange coefficient in a Lagrange function of an optimization problem established by designing a suitable precoding matrix and decoding matrix. By introducing the Lagrange multiplier, the originally constrained optimization problem can be converted into an unconstrained optimization problem, thereby simplifying the process of solving the optimization problem, so as to obtain a suitable precoding matrix and decoding matrix, which can minimize the sum of the mean square errors of the actual received uplink data and the target uplink data of the access network device of each cell in the plurality of cells, and improve the accuracy of the received data of the access network device.

[0031] In a possible implementation of the second aspect, the first terminal calculates the n+1 th round first precoding matrix of the first cell based on the n th round decoding matrix of the plurality of cells, the second precoding matrix of each terminal in the first cell, the equivalent channel matrix between each terminal in the first cell and the access network device of the plurality of cells and the variance of the channel estimation error between each terminal in the plurality of cells and the first access network device, and the plurality of Lagrange multipliers, including:

[0032] ;

[0033] Wherein, H jk i represents the equivalent channel matrix between the j th cell and the k th terminal and the access network device of the i th cell, , denotes a channel estimation matrix between the kth terminal in the jth cell and the access network device in the ith cell, denotes a second precoding matrix of the kth terminal in the jth cell, denotes a conjugate transpose of an equivalent channel matrix between the kth terminal in the jth cell and the access network device in the ith cell, denotes a decoding matrix of the ith cell in the nth round, denotes a conjugate transpose of a decoding matrix of the ith cell in the nth round, denotes a variance of a channel estimation error between the kth terminal in the jth cell and the access network device in the ith cell, denotes a trace of the matrix in the parentheses, denotes a conjugate matrix of the second precoding matrix of the kth terminal in the jth cell, denotes a Lagrange multiplier of the jth cell, denotes a unit matrix, denotes a conjugate transpose of an equivalent channel matrix between the kth terminal in the jth cell and the access network device in the jth cell, denotes a decoding matrix of the jth cell in the nth round, i, j = 1, …, Ku, k = 1, …, Ka, there are Ku cells in total, and there are Ka terminals in each cell. The iteration formula can gradually correct the error of the first precoding matrix by updating the first precoding matrix of the first cell in the (n+1)th round for multiple times, so as to obtain a more suitable first precoding matrix.

[0034] In a possible implementation manner of the second aspect, the first precoding matrix of the first cell in the first round is a randomly generated Mxd matrix satisfying the quasi-unitary constraint.

[0035] It should be noted that the specific content of the precoding matrix, the first precoding matrix, the second precoding matrix, the number of antennas, the uplink data and the like in the first access network device and the first terminal in the second aspect and any possible implementation manner thereof can be referred to the related description in the first aspect and any possible implementation manner thereof, which will not be described here.

[0036] In a third aspect, a method for data transmission based on over-the-air computation of channel estimation is provided. The method is applied to a first access network device, and the first access network device corresponds to a first cell. In the method, the first access network device can receive an nth round of precoding matrices from terminals in multiple cells. The multiple cells include the first cell, and the nth round of precoding matrices of a first terminal in the first cell includes an nth round of first precoding matrices of the first cell and a second precoding matrix of the first terminal, where n is sequentially taken from a set {1, 2, 3,..., N-1}. The first precoding matrix of the first cell in the first round is a random matrix satisfying a quasi-unitary constraint, the conjugate transpose of the matrix satisfying the quasi-unitary constraint multiplied by the matrix satisfying the quasi-unitary constraint equals a unit matrix, and the matrix satisfying the quasi-unitary constraint is an Mxd matrix. The second precoding matrix of the first terminal is an inverse matrix of a channel estimation matrix between the first terminal and the first access network device.

[0037] Then, the first access network device can calculate an nth round of decoding matrices of the first cell based on the nth round of first precoding matrices of the multiple cells, the second precoding matrices of the terminals in the multiple cells, equivalent channel matrices between the terminals in the multiple cells and the first access network device, variances of channel noise superimposed in channels between the terminals in the multiple cells and the first access network device, and variances of channel estimation errors between the terminals in the multiple cells and the first access network device. Moreover, the equivalent channel matrices are products of channel estimation matrices between the terminals in the multiple cells and the first access network device and corresponding second precoding matrices. The multiple cells include the first cell and other cells.

[0038] After the first access network device calculates the nth round of decoding matrices of the first cell, the first access network device sends the nth round of decoding matrices of the first cell to the first terminal. The nth round of decoding matrices of the first cell is used by the first terminal to calculate an nth+1 round of first precoding matrices of the first cell. The nth+1 round of precoding matrices of the first terminal includes the nth+1 round of first precoding matrices of the first cell and the second precoding matrix of the first terminal.

[0039] In the method, the decoding matrix calculated by the first access network device in each round is calculated according to the optimization result of the precoding matrix in the round, so that the error of the decoding matrix calculated by the first access network device in the last round can be corrected step by step. Moreover, the first access network device calculates the decoding matrix in the n th round of the first cell, not only referring to the precoding matrix in the n th round of each terminal in the first cell (including the first precoding matrix and the second precoding matrix), but also referring to the precoding matrix in the n th round of each terminal in the cells other than the first cell. Therefore, after N rounds of interaction, the decoding matrix in the N th round obtained finally can more accurately decode the uplink signal received by the first access network device, and improve the accuracy of the signal received by the first access network device. At the same time, the first access network device uses such a decoding matrix, so that the interference signal received by the first access network device from the cells other than the first cell is minimized, so that the influence of the channel estimation error and the channel noise during signal transmission is minimized, thereby improving the accuracy of uplink signal transmission of terminals in each cell.

[0040] In a possible implementation manner of the third aspect, after the first access network device calculates the decoding matrix in the n th round of the first cell, the first access network device can further receive the precoding matrix in the N th round of the terminals from the multiple cells. The precoding matrix in the N th round of the first terminal includes the first precoding matrix in the N th round of the first cell and the second precoding matrix of the first terminal. Then, the first access network device can calculate the decoding matrix in the N th round of the first cell based on the first precoding matrix in the N th round of the multiple cells, the second precoding matrix of each terminal in the multiple cells, the equivalent channel matrix between each terminal in the multiple cells and the first access network device, the variance of the channel noise superimposed in the channel between each terminal in the multiple cells and the first access network device, and the variance of the channel estimation error between each terminal in the multiple cells and the first access network device.

[0041] It should be noted that the precoding matrix, the first precoding matrix, the second precoding matrix, the number of antennas in the first access network device and the first terminal, the uplink data, and the specific method and formula of the first access network device calculating the decoding matrix in the n th round in the third aspect and any possible implementation manner thereof can refer to the related description in the first aspect and any possible implementation manner thereof, which will not be described here.

[0042] In a fourth aspect, a method for data transmission based on over-the-air computation of channel estimation is provided. The method is applied to a first terminal, which is a terminal of a first cell. In the method, the first terminal can obtain an nth round precoding matrix of the first terminal, and send the nth round precoding matrix of the first terminal to a first access network device. The nth round precoding matrix of the first terminal includes an nth round first precoding matrix of the first cell and a second precoding matrix of the first terminal, and n is sequentially taken from a set {1, 2, 3, …, N-1}. The first round first precoding matrix of the first cell is a random matrix satisfying a quasi-unitary constraint. The conjugate transpose of the matrix satisfying the quasi-unitary constraint multiplied by the matrix satisfying the quasi-unitary constraint equals a unit matrix. The matrix satisfying the quasi-unitary constraint is an Mxd matrix. The second precoding matrix of the first terminal is an inverse matrix of a channel estimation matrix between the first terminal and the first access network device of the first cell.

[0043] Then, the first terminal receives an nth round decoding matrix of the first cell from the first access network device. The nth round decoding matrix of the first cell is calculated based on an nth round first precoding matrix of multiple cells, a second precoding matrix of each terminal in the multiple cells, an equivalent channel matrix between each terminal in the multiple cells and the first access network device, a variance of channel noise superimposed in a channel between each terminal in the multiple cells and the first access network device, and a variance of channel estimation error between each terminal in the multiple cells and the first access network device. The equivalent channel matrix is a product of a channel estimation matrix between each terminal in the multiple cells and the first access network device and a corresponding second precoding matrix. The multiple cells include the first cell and other cells.

[0044] After the first terminal receives the nth round decoding matrix of the first cell from the first access network device, the first terminal can calculate an (n+1)th round first precoding matrix of the first cell based on an nth round decoding matrix of the multiple cells, a second precoding matrix of each terminal in the first cell, an equivalent channel matrix between each terminal in the first cell and access network devices of the multiple cells, a variance of channel estimation error between each terminal in the multiple cells and the first access network device, and multiple Lagrange multipliers. The (n+1)th round precoding matrix of the first terminal includes an (n+1)th round first precoding matrix of the first cell and a second precoding matrix of the first terminal.

[0045] In the method, each round of precoding matrix (including the first precoding matrix and the second precoding matrix) calculated by the first terminal is calculated according to the optimization result of the decoding matrix of the last round, so as to realize step-by-step correction of the error of the precoding matrix calculated by the first terminal in the last round. Moreover, the calculation of the precoding matrix of the n+1th round of the first cell not only refers to the decoding matrix of the n th round of the first cell, but also refers to the decoding matrix of the n th round of the cells other than the first cell. Therefore, after N rounds of interaction, the precoding matrix of the N th round finally obtained can better match the decoding requirements of the receiving end, more accurately adapt to the current channel state, and optimize the signal transmission performance. At the same time, the first terminal adopts such a precoding matrix to realize the alignment of the uplink interference signals of other cells, so as to facilitate the first access network device to better suppress the interference signals.

[0046] It should be noted that the precoding matrix, the first precoding matrix, the second precoding matrix, the number of antennas, the uplink data in the first access network device and the first terminal in the fourth aspect and any possible implementation manner thereof can refer to the related description in the first aspect and any possible implementation manner thereof, which will not be repeated here.

[0047] The specific method and formula for the first terminal to calculate the n th round of precoding matrix in the fourth aspect and any possible implementation manner thereof can refer to the related description in the second aspect and any possible implementation manner thereof, which will not be repeated here.

[0048] In a fifth aspect, a communication apparatus is provided, the communication apparatus comprising one or more processors; the one or more processors configured to execute computer programs or instructions, when the one or more processors execute the computer programs or instructions, the method according to any one of the first aspect to the fourth aspect is executed.

[0049] In a possible implementation manner of the fifth aspect, the communication apparatus further comprises one or more memories, the one or more memories coupled to the one or more processors, and the one or more memories configured to store the computer programs or instructions. In a possible implementation manner, the memory is located outside the communication apparatus. In another possible implementation manner, the memory is located inside the communication apparatus. In this application, the processor and the memory can also be integrated into one device, that is, the processor and the memory can also be integrated together. In a possible implementation manner, the communication apparatus further comprises a transceiver, the transceiver configured to receive information and / or send information.

[0050] In a possible design, the communication apparatus further comprises one or more communication interfaces, the one or more communication interfaces coupled to the one or more processors, and the one or more communication interfaces configured to communicate with other modules outside the communication apparatus.

[0051] In a sixth aspect, the present application provides a communication apparatus, comprising an interface circuit and a logic circuit; the interface circuit is configured to input and / or output information; the logic circuit is configured to perform the method according to any one of the first aspect to the fourth aspect, process and / or generate information according to the information.

[0052] In a seventh aspect, the present application provides a computer readable storage medium, which stores computer instructions or programs, when the computer instructions or programs are run on a computer, the method according to any one of the first aspect to the fourth aspect is performed.

[0053] In an eighth aspect, the present application provides a chip, comprising: a processor, and a memory coupled to the processor, the memory is configured to store programs or instructions, when the programs or instructions are executed by the processor, the method according to any one of the first aspect to the fourth aspect is performed.

[0054] In a ninth aspect, the present application provides a computer program product comprising computer instructions, when the computer instructions are run on a computer, the method according to any one of the first aspect to the fourth aspect is performed.

[0055] In a tenth aspect, the present application provides a communication system, comprising a communication apparatus for implementing the method according to any one of the first aspect to the fourth aspect.

[0056] The technical effects brought by any one of the fifth aspect to the tenth aspect can refer to the technical effects brought by any one of the first aspect to the fourth aspect, which will not be repeated. BRIEF DESCRIPTION OF DRAWINGS

[0057] Figure 1 A schematic diagram of a communication system architecture provided by an embodiment of the present application;

[0058] Figure 2 A schematic diagram of an interference model of a three-cell aerial computing system provided by an embodiment of the present application;

[0059] Figure 3 A schematic diagram of a data transmission method based on aerial computing provided by an embodiment of the present application;

[0060] Figure 4 A schematic diagram of a code matrix determination method provided by an embodiment of the present application;

[0061] Figure 5 A detailed step decomposition schematic diagram of a code matrix determination method provided by an embodiment of the present application Figure 1 ;

[0062] Figure 6 A detailed step decomposition schematic diagram of a code matrix determination method provided by an embodiment of the present applicationFigure 2 ;

[0063] Figure 7 A detailed step decomposition diagram of a coding and decoding matrix determination method provided for an embodiment of the application Figure 3 ;

[0064] Figure 8 A detailed step decomposition diagram of a coding and decoding matrix determination method provided for an embodiment of the application Figure 4 ;

[0065] Figure 9 A detailed step decomposition diagram of a coding and decoding matrix determination method provided for an embodiment of the application Figure 5 ;

[0066] Figure 10 A method diagram for obtaining a precoding matrix, a decoding matrix, and a Lagrange multiplier provided for an embodiment of the application

[0067] Figure 11 An analysis block diagram of a three-cell over-the-air computing system provided for an embodiment of the application

[0068] Figure 12 A structure diagram of a communication device provided for an embodiment of the application

[0069] Figure 13 A structure diagram of another communication device provided for an embodiment of the application. DETAILED DESCRIPTION

[0070] The technical solutions in the embodiments of the application will be described below with reference to the accompanying drawings.

[0071] The over-the-air computing-based technical solutions of the embodiments of the application can be applied to a future 6G mobile communication system, and other mobile communication systems that may appear in the future. Figure 1 An architecture diagram of a communication system provided for an embodiment of the application. As shown in Figure 1 , the communication system can include at least one terminal, such as the terminal 100 shown in Figure 1 ; the communication system can also include at least one access network device, such as the access network device 101 shown in Figure 1 . The terminal 100 and the access network device 101 can transmit signals between each other, wherein the access network device 101 sends signals to the terminal 100 is called downlink (DL) data transmission (or downlink communication), and the terminal 100 sends signals to the access network device 101 is called uplink (UL) data transmission (or uplink communication). The technical solutions provided by the application can be applied to uplink data transmission.

[0072] It should be understood thatFigure 1 More network nodes, such as more terminals or access network devices, can also be included in the illustrated communication system, which are not shown in the figure.

[0073] The terminal in the embodiments of the present application can refer to a user equipment (UE), a station, an access terminal, a user unit, a user station, a mobile station, a mobile station, a remote station, a remote terminal, a mobile device, a user terminal, a wireless communication device, a user agent or a user device. The terminal can also be a cellular phone, a cordless phone, a session initiation protocol (SIP) phone, a wireless local loop (WLL) station, a personal digital assistant (PDA), a handheld device with wireless communication function, a computing device or other processing device connected to a wireless modem, a vehicle-mounted device, a wearable device, a terminal in a 5G network or a terminal in a future evolved public land mobile network (PLMN), etc. The embodiments of the present application do not limit the form of the terminal.

[0074] The access network device in the present application is also sometimes referred to as an access point. The access network device includes but is not limited to a base station in a communication system, an evolved NodeB (eNodeB), a transmission reception point (TRP), a next generation NodeB (gNB) in a 5G mobile communication system, an access network device or a module of an access network device in an open access network (ORAN) system, a satellite in an NTN communication system, a base station in a future mobile communication system or an access point in a WiFi system, etc. The base station can communicate with the terminal, or communicate with the terminal through a relay station. The terminal can communicate with multiple base stations in different access technologies. The embodiments of the present application do not limit the specific technology and specific device form adopted by the access network device.

[0075] The access network device and / or the terminal can be fixed or mobile. The access network device and / or the terminal can be deployed on land, including indoors or outdoors, handheld or vehicle-mounted; can also be deployed on the water surface; and can also be deployed on an airplane, a balloon, and a man-made satellite in the air. Embodiments of the present application do not limit the application scenarios of the access network device and the terminal. The access network device and the terminal can be deployed in the same scenario or different scenarios, for example, the access network device and the terminal are both deployed on land; or the access network device is deployed on land and the terminal is deployed on the water surface, and the like, which will not be listed one by one.

[0076] To facilitate understanding of the embodiments of the present application, first, the terms involved in the present application are briefly explained. Optionally, the explanation of some terms can also refer to the explanation in the 3GPP standard protocol.

[0077] 1. AirComp

[0078] AirComp is a technology that utilizes the superposition characteristics of a wireless channel to realize the fusion of communication and computation. The fusion of communication and computation specifically means that a computing task can be directly completed in the communication process. AirComp can apply function computation to the signals sent by multiple transmitting ends (such as terminals) received by a receiving end (such as an AP), utilize the superposition of the signals, so that the receiving end (such as the AP) can obtain the function computation result of the signals. For example, the transmitting end can send data, and the receiving end can receive the sum of the data after the wireless channel; the transmitting end can send the square of the data, and the receiving end can receive the sum of the square of the data after the wireless channel, or can take the square root of the received sum of the square of the data to obtain the root mean square computation result.

[0079] 2. Interference alignment

[0080] Interference alignment is an interference management technology for a multi-antenna multi-user wireless communication system. The core idea is to design a precoding matrix at the transmitting end to align the interference signals in a limited dimension, and then design a decoding matrix at the receiving end to completely eliminate the influence of the interference signals on the expected signals.

[0081] 3. Precoding matrix

[0082] The precoding matrix is a technology for a multi-antenna communication system, which linearly transforms the signal at the transmitting end to suppress the interference or distortion of the signal in the transmission process.

[0083] 4. Decoding matrix

[0084] The decoding matrix is a matrix used for decoding the received signal at the receiving end, which restores the original data through a linear or nonlinear algorithm, maximizes the signal-to-noise ratio, or minimizes the bit error rate.

[0085] It should be understood that the technical terms in this application are only used as examples and are not limited. For example, as technology evolves, technical terms may also change, and other technical terms should also apply to this application in the case of the same technical meaning.

[0086] In the AirComp system, there can be multiple cells, and the access network device of each cell can not only receive the uplink data sent by the terminals in the cell, but also receive the uplink interference data sent by the terminals in other cells. As shown in Figure 2 It shows an interference model diagram of a three-cell AirComp system.

[0087] As shown in Figure 2 , the three cells are cell A, cell B, and cell C, respectively, and each cell is composed of an access network device and Ka terminals, that is, cell A includes access network device A, terminal A1, terminal A2, …, terminal AKa, cell B includes access network device B, terminal B1, terminal B2, …, terminal BKa, and cell C includes access network device C, terminal C1, terminal C2, …, terminal CKa.

[0088] For example, as shown in Figure 2 , taking cell A as an example, the process of uplink data transmission is described. Each terminal in cell A sends uplink data to access network device A, and the uplink data transmission process can realize AirComp according to the superposition characteristics of the wireless channel; correspondingly, access network device A can receive the AirComp result of the uplink data sent by each terminal in cell A. For example, terminals A1, A2, …, and Aka send uplink data, and access network device A will receive the sum of the uplink data sent by each terminal in cell A after transmission through the wireless channel. However, access network device A will also receive uplink interference data sent by each terminal in cell B and cell C, and the wireless channel carrying the uplink data transmission will have fading, noise, etc., which will cause the sum of the uplink data sent by each terminal in cell A received by access network device A to be inaccurate, affecting the accuracy of uplink data transmission.

[0089] In actual communication systems, in order to compensate for and overcome the effects of fading, noise, and interference, etc., the terminal can use a precoding matrix to adjust the amplitude and phase of the uplink data to send the uplink signal, so as to compensate for the effects of channel fading, etc., so that the access network device can better perform signal superposition and calculation. The access network device can use a decoding matrix to suppress the interference of external signals, separate the data of each sending terminal from the superimposed signals, or directly obtain the expected calculation result, overcoming the effects of noise and interference. The generation of the precoding matrix and the decoding matrix is based on the channel state information between the terminal and the access network device.

[0090] However, the terminal and the access network device often cannot have accurate channel state information, but can only have estimated or measured channel state information. In the case of inaccurate channel state information, the uplink interference data from the terminals of other cells cannot be accurately aligned in phase and amplitude, and the residual uplink interference data will leak to the receiving space of the uplink data of the terminals of the cell, thereby reducing the accuracy of the function calculation result (such as the sum of the uplink data) of the uplink data of the terminals of the cell received by the access network device of the cell.

[0091] Therefore, how to reduce the influence of wireless channel fading, noise, and uplink interference data of other cells received by the access network device of each cell in the AirComp system composed of multiple cells based on the inaccurate channel state information obtained by estimation or measurement, and improve the accuracy of the uplink data transmission of the terminals of each cell, is a problem to be solved.

[0092] In the related art, method one provides a relay-assisted double-network AirComp method under inaccurate channel state information. The AirComp process is completed in two time slots. In the first time slot, each sensor (terminal) in the first network (or cell) transmits a signal to the amplify-and-forward relay and the data fusion center AP1 (access network device), and each sensor (terminal) in the second network (or cell) transmits a signal to the amplify-and-forward relay and the data fusion center AP2 (access network device). In the second time slot, the amplify-and-forward relay forwards the signal to the data fusion center AP1 and the data fusion center AP2; the results obtained by the AP1 and the AP2 by receiving the signals in the two time slots and performing calculation are recorded as the actual received signals, the total mean square error of the double-network AirComp is obtained by calculating the mean square error of the AP1 and the AP2, thereby constructing the total mean square error minimization problem of the double-network AirComp. And the suboptimal solution of the total mean square error minimization problem is calculated by using the alternating optimization method, the final value of the total mean square error is obtained, and the total mean square error obtained by using the method is smaller, which can improve the accuracy of the AirComp of the two AirComp networks.

[0093] However, the above-mentioned method one is suitable for two networks, which can be understood as an AirComp network including two cells, and is not suitable for an AirComp system composed of multiple cells. Moreover, the terminal of the method transmits single-stream uplink data through a single antenna, and is not suitable for the terminal transmitting multi-stream uplink data through multiple antennas.

[0094] Method two studies the interference problem when air computing coexists with cellular communication. This method discusses the design of the receiving end aggregation vector under accurate channel information, and proposes a joint optimization algorithm based on MMSE for air computing network and cellular system. The algorithm performs well in convergence speed and stability, but in practical application, it still needs to make a trade-off between improving the data aggregation accuracy of air computing and ensuring the signal quality of cellular communication.

[0095] The above-mentioned method two is suitable for the case where the terminal and the access network device have accurate channel state information, and is suitable for interference data elimination between one air computing network and one non-air computing network (i.e. cellular communication network), and the terminal transmits single-stream uplink data through a single antenna, and is not suitable for an air computing system composed of multiple cells and multiple-stream uplink data transmitted through multiple antennas.

[0096] Based on this, the embodiment of the present application provides a data transmission method based on channel estimation of air computing. The terminal can process uplink data by using a double-layer precoding matrix, and then send the uplink signal obtained after processing the uplink data to the access network device. The access network device can decode the uplink signal by using the decoding matrix of the access network device to obtain the uplink data. In this scheme, the double-layer precoding matrix and the decoding matrix used by the terminal can not only make the access network devices of each cell in the AirComp system correctly receive the function calculation results (such as the sum of the uplink data) of the uplink data sent by the terminals of each cell, but also minimize the uplink interference data sent by the terminals from other cells, while reducing the influence of channel estimation error and noise, and improving the accuracy of terminal uplink data transmission.

[0097] The scheme provided by the present application will be described in detail below in conjunction with the corresponding flowchart. It can be understood that the main devices (such as terminals, access network devices) in the illustrative flowchart are taken as an example to illustrate the execution subject of the interaction, but the present application does not limit the execution subject of the interaction. For example, the devices (such as terminals, access network devices) in the illustrative flowchart can also be chips, chip systems, or processors supporting the implementation of the method by the device, and can also be logical modules or software capable of realizing all or part of the functions of the device.

[0098] The embodiment of the present application provides a data transmission method based on channel estimation of air computing, as shown in Figure 3 The method can include S301-S304:

[0099] S301, the first terminal acquires the precoding matrix of the first terminal.

[0100] Wherein, the first terminal is the terminal of the first cell, as Figure 2The precoding matrix of the first terminal comprises a first precoding matrix of the first cell and a second precoding matrix of the first terminal. The first precoding matrices of different terminals in the same cell are the same. Therefore, in the embodiments of the present application, the first precoding matrix of a terminal is referred to as the first precoding matrix of the cell where the terminal is located. It should be understood that terminals in different cells will interfere with each other, especially in the edge area of the cell. By designing different first precoding matrices for terminals in different cells, the interference between cells can be coordinated, and the performance of the entire system can be improved.

[0101] The first precoding matrix of the first cell is different from the first precoding matrix of other cells. The second precoding matrix of the first terminal is different from the second precoding matrix of other terminals in the first cell, and the second precoding matrix of the first terminal is different from the second precoding matrix of terminals in other cells. Since the wireless channel is affected by various factors, the channel characteristics between different terminals and the same access network device are different, so designing different second precoding matrices according to the respective channel characteristics can enable the signal of each terminal to be correctly received and decoded at the access network device.

[0102] The first precoding matrix of the first cell is used to align the uplink interference data received by the first access network device from other cells in the plurality of cells. The first access network device is the access network device of the first cell. The second precoding matrix of the first terminal is used to align the uplink data transmitted by each terminal in the first cell to the first access network device. The plurality of cells comprises the first cell and other cells.

[0103] Through the design of the above-mentioned double-layer precoding matrix (such as the first precoding matrix and the second precoding matrix), the desired signal and the interference signal can be distinguished at the receiving end, and the first access network device can more effectively identify and extract the desired signal, thereby reducing the impact of inter-cell interference on system performance and improving signal reception quality.

[0104] In the embodiments of the present application, the first terminal is configured with multiple antennas, and the uplink data transmitted by the first terminal to the first access network device is multi-stream data. For example, the first terminal is configured with M antennas, and the uplink data is multi-stream data, which comprises d data streams. The precoding matrix of the first terminal is an Mxd matrix. Specifically, the first precoding matrix of the first cell is an Mxd matrix, and the second precoding matrix of the first terminal is an MxM matrix. The design of multiple antennas makes the present scheme applicable to single antenna or single stream data transmission, as well as multiple antenna or multi-stream data transmission.

[0105] The first precoding matrix of the first cell is calculated based on a decoding matrix of multiple cells, a second precoding matrix of each terminal in the first cell, an equivalent channel matrix between each terminal in the first cell and access network devices of the multiple cells, and a variance of channel estimation error between each terminal in the multiple cells and the first access network device, and multiple Lagrange multipliers. The specific method for the first terminal to obtain the precoding matrix of the first terminal in S301 can refer to the related description in the following embodiments, and will not be described here again.

[0106] In S302, the first terminal sends an uplink signal to the first access network device, and the first access network device receives the uplink signal from the first terminal.

[0107] The uplink signal is encoded by the precoding matrix of the first terminal.

[0108] For example, the terminal A1 in the cell A sends an uplink signal. Figure 2 The terminal A1 in the cell A has 2 antennas, and the uplink data sent by the terminal A1 has 2 data streams. The first precoding matrix of the cell A is , and the uplink signal encoded by the first precoding matrix of the cell A is The second precoding matrix of the cell A is , and the uplink signal encoded by the second precoding matrix of the cell A is .

[0109] In S303, the first access network device obtains a decoding matrix of the first access network device.

[0110] The decoding matrix of the first access network device is used to decode the uplink signal to obtain the uplink data.

[0111] The first access network device has M antennas configured to receive the uplink signal sent by the first terminal through the M antennas, and the decoding matrix is an Mxd matrix.

[0112] The decoding matrix of the first access network device is calculated based on the first precoding matrix of the multiple cells, the second precoding matrix of each terminal in the multiple cells, the equivalent channel matrix between each terminal in the multiple cells and the first access network device, the variance of the channel noise superimposed in the channel between each terminal in the multiple cells and the first access network device, and the variance of the channel estimation error between each terminal in the multiple cells and the first access network device. The specific method for the first access network device to obtain the decoding matrix of the first access network device in S303 can refer to the related description in the following embodiments, and will not be described here again.

[0113] S304, the first access network device decodes the uplink signal by using the decoding matrix of the first access network device to obtain uplink data.

[0114] The decoding matrix of the first access network device not only refers to the precoding matrixes (including the first precoding matrix and the second precoding matrix) of the terminals in the cell, but also refers to the precoding matrixes of the terminals in other cells. Therefore, the first access network device uses such a decoding matrix to improve the accuracy of the received target signal of the first access network device, minimize the interference signal received by the first access network device from other cells except the first cell, and minimize the error caused by the channel estimation error and the influence of the channel noise during signal transmission.

[0115] For example, the access network device in the cell A is configured with two antennas, and the uplink signal received by the access network device after wireless channel transmission is The decoding matrix is The conjugate transpose of the decoding matrix is Then, the uplink data obtained by the uplink signal through the decoding matrix of the first access network device is .

[0116] Through the method of the embodiment of the present application, the uplink data sent by the terminal (such as the first terminal) through the first precoding matrix can align the uplink interference data received by the corresponding access network device (such as the first access network device) in the cell (such as the first cell) from other cells except the cell. Then, the uplink data is further processed by the second precoding matrix of the terminal (such as the first terminal), so that the uplink data sent by each terminal in the cell (such as the first cell) to the corresponding access network device (such as the first access network device) is aligned. The double-layer precoding matrix (including the first precoding matrix and the second precoding matrix) obtained by the terminal (such as the first terminal) after N rounds of interactive iteration not only refers to the decoding matrix of the cell, but also refers to the decoding matrix of other cells. Therefore, the uplink signal encoded by the double-layer precoding matrix (including the first precoding matrix and the second precoding matrix) can make the expected signal and the interference signal have distinguishability at the receiving end.

[0117] The access network device (such as the first access network device) receives the uplink signal from the terminal (such as the first terminal), decodes the uplink signal using a decoding matrix to obtain the uplink data. The decoding matrix used by the access network device not only refers to the precoding matrix (including the first precoding matrix and the second precoding matrix) of each terminal (such as the first terminal) in the cell, but also refers to the precoding matrix of each terminal in other cells. Moreover, the decoding matrix obtained by the access network device after N rounds of interactive iteration can minimize the sum of the mean square errors of the actual received uplink data and the target uplink data of the access network device in each cell in multiple cells. Therefore, the decoding matrix can minimize the interference of the uplink data signal from other cells while ensuring that the access network device in the cell correctly receives the signal sent by the terminal in the cell, and can minimize the influence of the channel estimation error and noise between each terminal in multiple cells and the access network device in each cell, thereby improving the accuracy of the uplink data transmission of the terminal in each cell.

[0118] The above describes a data transmission method based on channel estimation by air computing. The method can be applied not only to an air computing system of two cells, but also to an air computing system of three or more cells. The present application embodiment also includes a method for obtaining a precoding matrix and a decoding matrix in the data transmission method based on channel estimation by air computing, that is, a coding and decoding matrix determination method.

[0119] For example, the coding and decoding matrix determination method provided by the present application embodiment is described below with reference to the access network devices and terminals in the three cells shown in Figure 2 The coding and decoding matrix determination method provided by the present application embodiment, and the specific way for the terminal to obtain the precoding matrix (i.e., S301) and the specific way for the access network device to obtain the decoding matrix (i.e., S303) in the above uplink data transmission method based on air computing are described below with reference to the access network devices and terminals in the three cells shown in

[0120] As shown in Figure 2 There are two terminals in each cell, i.e., terminal A1 and terminal A2 in cell A, terminal B1 and terminal B2 in cell B, and terminal C1 and terminal C2 in cell C. The access network device A of cell A can interact with the terminal A1 and the terminal A2 in cell A to determine the decoding matrix of the access network device A (which can also be referred to as the decoding matrix of cell A) and the precoding matrix of the terminal A1 and the terminal A2. As shown in Figure 2 The access network device B of cell B can interact with the terminal B1 and the terminal B2 in cell B to determine the decoding matrix of the access network device B (which can also be referred to as the decoding matrix of cell B) and the precoding matrix of the terminal B1 and the terminal B2. As shown in Figure 2As shown, the access network device C of the cell C can interact with the terminal C1 and the terminal C2 in the cell C to determine the decoding matrix of the access network device C (which can also be referred to as the decoding matrix of the cell C) and the terminal C1 and the terminal C2 determine their precoding matrices. In the embodiments of the present application, the interaction between the access network device A of the cell A and the terminal A1 and the terminal A2 in the cell A is mainly taken as an example to introduce the method of the embodiments of the present application.

[0121] It should be noted that in the embodiments of the present application, the terminal and the corresponding access network device need to interact for N rounds to obtain the precoding matrix and the decoding matrix that can achieve interference alignment. For example, N can be any value such as 50, 100, 150, 200, 300, 350, etc. In the initial iteration of the interaction between the access network device and the terminal (for example, N is any value in 50 to 100), the optimization direction of the first precoding matrix and the decoding matrix is clear, and as the number of iterations increases, the sum of the mean square errors of the actual received uplink data and the target uplink data of the access network device of each cell in multiple cells will significantly decrease. However, the larger N is, the smaller the decrease of the sum of the mean square errors will be. Generally, around 250-300 rounds, the algorithm approaches convergence, and the performance improvement of the continued iteration is limited, and more rounds will significantly increase the calculation time, power consumption and hardware resource occupation. N is generally an empirical value of 250-300, and after 250-300 rounds of alternating iteration, the precoding matrix and the decoding matrix obtained by calculation have good interference alignment effect. In particular, N=300. The precoding matrix of each terminal in the embodiments of the present application is a double-layer precoding matrix, including the first precoding matrix and the second precoding matrix.

[0122] For example, as shown in FIG. 3, Figure 4 As shown, the coding and decoding matrix determination method can include N rounds of interaction processes such as process (1) to process (5). The steps S301 and S303 can also include N rounds of interaction processes such as process (1) to process (5). Process (1): the first round of precoding matrix determination process. Process (2): the first round of decoding matrix determination process. Process (3): the second round of precoding matrix determination process. Process (4): the second round of decoding matrix determination process. Process (5): the third round of precoding matrix determination process. Referring to process (4) of the second round of decoding matrix determination, the qth round of decoding matrix determination process can be performed, where q is sequentially taken from the set {3, 4, …, N}. Referring to process (5) of the third round of precoding matrix determination, the pth round of precoding matrix determination process can be performed, where p is sequentially taken from the set {4, 5, …, N}. Until the Nth round of interaction process is completed, the Nth round of first precoding matrix and the Nth round of decoding matrix are obtained, that is, the precoding matrix and the decoding matrix that can achieve interference alignment are obtained.

[0123] In the embodiments of the present application, the precoding matrix of the terminal is a double-layer precoding matrix, including a first precoding matrix and a second precoding matrix.

[0124] For example, the precoding matrix of terminal A1 (e.g., a first terminal) of cell A (e.g., a first cell) is The precoding matrix includes the first precoding matrix of terminal A1 of cell A and the second precoding matrix of terminal A1 of cell A , .

[0125] The precoding matrix of terminal A2 (e.g., a second terminal) of cell A is The precoding matrix includes the first precoding matrix of terminal A2 of cell A and the second precoding matrix of terminal A2 of cell A , .

[0126] The precoding matrix of terminal B1 of cell B (e.g., a second cell) is The precoding matrix includes the first precoding matrix of terminal B1 of cell B and the second precoding matrix of terminal B1 of cell B , .

[0127] The precoding matrix of terminal B2 of cell B is The precoding matrix includes the first precoding matrix of terminal B2 of cell B and the second precoding matrix of terminal B2 of cell B , .

[0128] The precoding matrix of terminal C1 of cell C is The precoding matrix includes the first precoding matrix of terminal C1 of cell C and the second precoding matrix of terminal C1 of cell C , .

[0129] The precoding matrix of terminal C2 of cell C is The precoding matrix includes the first precoding matrix of terminal C2 of cell C and the second precoding matrix of terminal C2 of cell C , and .

[0130] The first precoding matrix is ​​used to align uplink interference data received by the first access network device from other cells in a plurality of cells. The second precoding matrix is ​​used to align uplink data sent by each terminal in the first cell to the first access network device.

[0131] For example, taking cell A as the first cell, terminal A1 as the first terminal, and access network device A as the first access network device, the first precoding matrix of terminal A1 is used to align the uplink interference data received by access network device A from cell B and cell C. The second precoding matrix of terminal A1 is used to align the uplink data sent by terminals A1 and A2 in cell A to access network device A.

[0132] like Figure 5 As shown, the above process (1), namely the "first round of precoding matrix determination process", may include S501-S502.

[0133] S501. Any terminal in the cell (such as terminal A1 or terminal A2 in cell A, terminal B1 or terminal B2 in cell B, terminal C1 or terminal C2 in cell C) generates the matrix that satisfies the pseudo-unitary constraint of the corresponding cell (i.e. the first precoding matrix of the first round).

[0134] For example, any terminal in a cell can randomly generate a matrix that satisfies the anamorphic unitary constraint for the corresponding cell. For instance, terminal A1 can randomly generate a matrix that satisfies the anamorphic unitary constraint for cell A, or terminal A2 can randomly generate a matrix that satisfies the anamorphic unitary constraint for cell A. Terminal B1 can randomly generate a matrix that satisfies the anamorphic unitary constraint for cell B, or terminal B2 can randomly generate a matrix that satisfies the anamorphic unitary constraint for cell B. Terminal C1 can randomly generate a matrix that satisfies the anamorphic unitary constraint for cell C, or terminal C2 can randomly generate a matrix that satisfies the anamorphic unitary constraint for cell C. The aforementioned matrix satisfying the anamorphic unitary constraint is the initialized first precoding matrix, i.e., the first precoding matrix for the first round.

[0135] It should be noted that the first precoding matrix changes in each round. For example, the first precoding matrix of terminal A1 in cell A is different from the first precoding matrix of terminal A1 in cell A in the second round, and the first precoding matrix of terminal B1 in cell B in the second round is different from the first precoding matrix of terminal B1 in cell B in the third round.

[0136] The first precoding matrix of each round of different terminals in the same cell is the same. For example, the first precoding matrix of the first round of terminal A1 and terminal A2 in cell A is the same, and the first precoding matrix of the second round of terminal A1 and terminal A2 in cell A is the same. The first precoding matrix of the first round of terminal B1 and terminal B2 in cell B is the same, and the first precoding matrix of the second round of terminal B1 and terminal B2 in cell B is the same. Therefore, the first precoding matrix of terminal A1 and terminal A2 can be called the first precoding matrix of cell A, the first precoding matrix of terminal B1 and terminal B2 can be called the first precoding matrix of cell B, and the first precoding matrix of terminal C1 and terminal C2 can be called the first precoding matrix of cell C.

[0137] The first precoding matrix of each round of terminals in different cells is different, which can also be understood as the first precoding matrix of each round in different cells being different. Since the terminals in different cells will interfere with each other, especially in the cell edge area. Therefore, by designing different first precoding matrices for terminals in different cells, the interference between cells can be coordinated, and the performance of the entire system can be improved. For example, the first precoding matrix of the first round of terminal A1 in cell A is different from the first precoding matrix of the first round of terminal B1 in cell B; the first precoding matrix of the first round of terminal C2 in cell C is different from the first precoding matrix of the first round of terminal B1 in cell B. The second round of the first precoding matrix of terminal A1 in cell A is different from the second round of the first precoding matrix of terminal B1 in cell B; the second round of the first precoding matrix of terminal C2 in cell C is different from the second round of the first precoding matrix of terminal B1 in cell B. Or, the first precoding matrix of the first round of cell A, cell B and cell C is different, and the first precoding matrix of the second round of cell A, cell B and cell C is different.

[0138] Here, the first terminal is terminal A1, the first cell is cell A, and terminal A1 randomly generates a matrix of cell A that satisfies the quasi-unitary constraint (i.e., the first precoding matrix of the first round of cell A ) as an example, the specific method of the terminal randomly generating a matrix that satisfies the quasi-unitary constraint is introduced.

[0139] Terminal A1 is configured with M antennas, and the uplink data transmitted by terminal A1 to the access network device is multi-stream data, which includes d data streams. That is, the present scheme can be used for single antenna or single stream data transmission, or can be applied to multi-antenna or multi-stream data transmission. Terminal A1 can randomly generate an Mxd matrix that satisfies the quasi-unitary constraint.

[0140] The conjugate transpose of the matrix satisfying the pseudo-unitary constraint multiplied by the matrix satisfying the pseudo-unitary constraint equals a unit matrix. The matrix satisfying the pseudo-unitary constraint indicates that column vectors of the matrix are orthogonal. Using the matrix satisfying the pseudo-unitary constraint to encode uplink data transmitted by the terminal A1 can make the uplink signal obtained after encoding maintain good orthogonality in the transmission process, thereby reducing interference of other cells on uplink transmission of the terminal signal of the cell, and improving transmission efficiency of the signal and decoding performance of the receiving end.

[0141] S502, a terminal (such as the terminal A1, the terminal A2, the terminal B1, the terminal B2, the terminal C1, and the terminal C2) acquires a second precoding matrix of the terminal.

[0142] For example, the terminal A1 can acquire the second precoding matrix of the terminal A1, the terminal A2 can acquire the second precoding matrix of the terminal A2, the terminal B1 can acquire the second precoding matrix of the terminal B1, the terminal B2 can acquire the second precoding matrix of the terminal B2, the terminal C1 can acquire the second precoding matrix of the terminal C1, and the terminal C2 can acquire the second precoding matrix of the terminal C2. The second precoding matrix is the second precoding matrix of the first round.

[0143] It should be noted that the second precoding matrix of each round is constant. For example, the second precoding matrix of the terminal A1 of the cell A in the first round is the same as the second precoding matrix of the terminal A1 of the cell A in the second round, and the second precoding matrix of the terminal B1 of the cell B in the second round is the same as the second precoding matrix of the terminal B1 of the cell B in the third round.

[0144] The second precoding matrices of different terminals in the same cell are different. For example, the second precoding matrices of the terminal A1 and the terminal A2 in the cell A are different, and the second precoding matrices of the terminal B1 and the terminal B2 in the cell B are different.

[0145] The second precoding matrices of terminals in different cells are different. For example, the second precoding matrix of the terminal A1 of the cell A is different from the second precoding matrix of the terminal B1 of the cell B, and the second precoding matrix of the terminal C2 of the cell C is different from the second precoding matrix of the terminal B1 of the cell B.

[0146] That is, different second precoding matrices are used for different terminals in the same cell, and different second precoding matrices are used for terminals in different cells. Through such a method, it can be considered that channel characteristics between different terminals and the same access network device are different, so different second precoding matrices are designed according to respective channel characteristics, which can enable signals of each terminal to be correctly received and decoded at the access network device.

[0147] The second precoding matrix of the terminal is an M x M matrix, and the second precoding matrix of the terminal is an inverse matrix of a channel estimation matrix between the terminal and the corresponding access network device. In this way, when the channel condition changes (such as user movement, environmental change, etc.), the channel estimation matrix is updated, and the second precoding matrix of the terminal is adjusted accordingly, so that the adjustment can dynamically adapt to the channel change, and the stability of the uplink signal transmission is maintained.

[0148] For example, the second precoding matrix of the terminal A1 is an inverse matrix of the channel estimation matrix between the terminal A1 and the access network device A. The second precoding matrix of the terminal A1 in the cell A can be expressed as , , wherein represents the channel estimation matrix between the terminal A1 and the access network device A, and is an M x M matrix.

[0149] Embodiments of the present application take the first terminal as the terminal A1, the first cell as the cell A, and the terminal A1 acquires the second precoding matrix of the terminal A1 (i.e., the second precoding matrix of the terminal A1 in each round) as an example, and introduce the specific method for the terminal to acquire the second precoding matrix of the terminal, including steps 1-3.

[0150] Step 1: The access network device A sends a pilot signal to the terminal A1, and correspondingly, the terminal A1 receives the pilot signal from the access network device A. Wherein, the pilot signal is used to help the terminal A1 to perform channel estimation, that is, to acquire the frequency response, phase, fading characteristics and other information of the channel. For example, the pilot signal includes cell-specific reference signal (CRS), demodulation reference signal (DM-RS), user-specific reference signal (URS), channel state information reference signal (CSI-RS), etc., which are not limited.

[0151] Step 2: After receiving the pilot signal, the terminal A1 can also compare it with the known pilot signal stored locally, calculate the channel response (such as amplitude, phase, time delay, etc.), and thus generate the channel estimation matrix between the terminal A1 and the access network device A (the channel estimation matrix from the access network device A to the terminal A1).

[0152] It should be noted that in the block fading channel, due to relatively slow channel change, if the uplink and downlink switching time interval is much smaller than the channel coherence time, it can be approximately considered that the uplink and downlink channels have reciprocity, and the downlink channel matrix can be used for uplink signal transmission, that is, the channel estimation matrix from the access network device A to the terminal A1 is equal to the channel estimation matrix from the terminal A1 to the access network device A, which can be referred to as the channel estimation matrix between the terminal A1 and the access network device A.

[0153] Step 3: The terminal A1 calculates the inverse matrix of the channel estimation matrix between the terminal A1 and the access network device A to obtain the second precoding matrix of the terminal A1.

[0154] Referring to the method of steps 1-3, each terminal can obtain the channel estimation matrix between the terminal and the corresponding access network device (for example, the terminal A2 obtains the channel estimation matrix between the terminal A2 and the access network device A, and the terminal B1 obtains the channel estimation matrix between the terminal B1 and the access network device B), so that each terminal can obtain the second precoding matrix of the terminal.

[0155] The following takes the access network device A and the terminals of multiple cells to interact to obtain the first round decoding matrix of the cell A as an example to introduce the method of the embodiments of the present application.

[0156] As shown in the above flow (2), that is, the first round decoding matrix determination flow, can include S601-S606.

[0157] S601, any terminal in the cell (such as the terminal A1 or the terminal A2 in the cell A, the terminal B1 or the terminal B2 in the cell B, or the terminal C1 or the terminal C2 in the cell C) sends the first round first precoding matrix of the corresponding cell to the access network device of the corresponding cell.

[0158] For example, the terminal A1 of the cell A sends the first round first precoding matrix of the cell A to the access network device A . Alternatively, the terminal A2 of the cell A sends the first round first precoding matrix of the cell A to the access network device A .

[0159] Similarly, the terminal B1 of the cell B sends the first round first precoding matrix of the cell B to the access network device B . Alternatively, the terminal B2 of the cell B sends the first round first precoding matrix of the cell B to the access network device B .

[0160] The terminal C1 of the cell C sends the first round first precoding matrix of the cell C to the access network device C . Alternatively, the terminal C2 of the cell C sends the first round first precoding matrix of the cell C to the access network device C . .

[0161] S602, the access network device A receives the first round of first precoding matrix of cell A, cell B and cell C.

[0162] For example, the access network device A receives the first round of first precoding matrix of cell A from terminal A1 of cell A.

[0163] It can be understood that the access network devices of each cell share all the first precoding matrix through the central unit (CU) connected with them. That is, the access network device A can also receive the first round of first precoding matrix of cell B and the first round of first precoding matrix of cell C.

[0164] Similarly, through the above method, the access network device B and the access network device C can also receive the first round of first precoding matrix of cell A, cell B and cell C.

[0165] S603, the terminals in the cells (such as terminal A1 and terminal A2 in cell A, terminal B1 and terminal B2 in cell B, terminal C1 and terminal C2 in cell C) send the second precoding matrix of the corresponding cell to the access network device of the corresponding cell.

[0166] For example, terminal A1 of cell A sends the second precoding matrix of terminal A1 to the access network device A , and terminal A2 of cell A sends the second precoding matrix of terminal A2 to the access network device A .

[0167] Similarly, terminal B1 of cell B sends the second precoding matrix of terminal B1 to the access network device B , and terminal B2 of cell B sends the second precoding matrix of terminal B2 to the access network device B .

[0168] Terminal C1 of cell C sends the second precoding matrix of terminal C1 to the access network device C , and terminal C2 of cell C sends the second precoding matrix of terminal C2 to the access network device C .

[0169] S604, the access network device A receives the second precoding matrix from the terminals (such as terminal A1, terminal A2, terminal B1, terminal B2, terminal C1 and terminal C2) of cell A, cell B and cell C.

[0170] For example, the access network device A receives the second precoding matrix of terminal A1 from cell A, and the access device A receives the second precoding matrix of terminal A2 from cell A.

[0171] It can be understood that the access network device of each cell shares all the second precoding matrices through the central unit (CU) connected with it by wire. That is, the access network device A can also receive the second precoding matrix of the terminal B1 of the cell B, the second precoding matrix of the terminal B2 of the cell B, the second precoding matrix of the terminal C1 of the cell C, and the second precoding matrix of the terminal C2 of the cell C.

[0172] Similarly, through the above method, the access network device B and the access network device C will also receive the second precoding matrices of the terminals (such as the terminal A1, the terminal A2, the terminal B1, the terminal B2, the terminal C1, and the terminal C2) of the cell A, the cell B, and the cell C.

[0173] S605, the access network device A obtains the equivalent channel matrix between each terminal in the cell A, the cell B, and the cell C and the access network device A, the variance of the channel noise superimposed in the channel between each terminal in the cell A, the cell B, and the cell C and the access network device A, and the variance of the channel estimation error between each terminal in the cell A, the cell B, and the cell C and the access network device A.

[0174] Wherein, the access network device A obtains the equivalent channel matrix between each terminal in the cell A, the cell B, and the cell C and the access network device A includes: obtaining the equivalent channel matrix between the terminal A1 of the cell A and the access network device A , obtaining the equivalent channel matrix between the terminal A2 of the cell A and the access network device A , obtaining the equivalent channel matrix between the terminal B1 of the cell B and the access network device A , obtaining the equivalent channel matrix between the terminal B2 of the cell B and the access network device A , obtaining the equivalent channel matrix between the terminal C1 of the cell C and the access network device A , and obtaining the equivalent channel matrix between the terminal C2 of the cell C and the access network device A .

[0175] Wherein, , is the channel estimation matrix between the terminal A1 of the cell A and the access network device A; , is the channel estimation matrix between the terminal A2 of the cell A and the access network device A; , is the channel estimation matrix between the terminal B1 of the cell B and the access network device A; , is the channel estimation matrix between the terminal B2 of the cell B and the access network device A; , is a channel estimation matrix between terminal C1 of cell C and access network device A; , is a channel estimation matrix between terminal C2 of cell C and access network device A, all terminals and all access network devices are configured with M antennas, the above equivalent channel matrix and channel estimation matrix are MxM matrices.

[0176] For example, access network device A obtains the equivalent channel matrix between terminal A1 of cell A and access network device A For example, the method that access network device A obtains the equivalent channel matrix between each terminal of cell A, cell B and cell C and access network device A is introduced.

[0177] In some embodiments, the equivalent channel matrix between terminal A1 of cell A and access network device A is sent by terminal A1 to access network device A. For example, terminal A1 can obtain the channel estimation matrix between terminal A1 and access network device A through steps 1-2 in step S502; terminal A1 obtains the second precoding matrix of terminal A1 through step S502; terminal A1 multiplies the channel estimation matrix between terminal A1 and access network device A and the second precoding matrix of terminal A1 to obtain the equivalent channel matrix between terminal A1 of cell A and access network device A . Terminal A1 sends the equivalent channel matrix between terminal A1 of cell A and access network device A to access network device A. Correspondingly, access network device A receives the equivalent channel matrix between terminal A1 of cell A and access network device A .

[0178] In this case, the equivalent channel matrix between each terminal of cell A, cell B and cell C and access network device A obtained in step S605 can be completed in step S502.

[0179] In some embodiments, the equivalent channel matrix between terminal A1 of cell A and access network device A may also be calculated by access network device A. For example, after terminal A1 obtains the channel estimation matrix between terminal A1 and access network device A through steps 1-2 in step S502, terminal A1 can send the channel estimation matrix between terminal A1 and access network device A to access network device A. Correspondingly, access network device A receives the channel estimation matrix between terminal A1 and access network device A Access network device A can receive the second precoding matrix of terminal A1 through step S604. Access network device A will compare the channel estimation matrix of terminal A1 in cell A with that of access network device A. The second precoding matrix of terminal A1 in cell A Multiplying these matrices yields the equivalent channel matrix between terminal A1 in cell A and access network device A. .

[0180] In this case, obtaining the equivalent channel matrix between each terminal in cell A, cell B, and cell C and access network device A in step S605 needs to be completed after step S604.

[0181] Referring to the above method, each terminal can obtain the channel estimation matrix from each terminal in cell A, cell B, and cell C to access network device A and the second precoding matrix of each terminal. Each terminal sends the channel estimation matrix and the second precoding matrix to the access network device in its respective cell. Each access network device shares the channel estimation matrix from each terminal to each access network device and the second precoding matrix of each terminal through the central unit connected to it by wire. Thus, access network device A can obtain the equivalent channel matrix between each terminal in cell A, cell B, and cell C and access network device A.

[0182] Similarly, access network device B will also obtain the equivalent channel matrix between each terminal in cell A, cell B, and cell C and access network device B. Access network device C will also obtain the equivalent channel matrix between each terminal in cell A, cell B, and cell C and access network device C.

[0183] Specifically, access network device A acquires the variance of the channel noise superimposed on the channel between each terminal in cell A, cell B, and cell C and access network device A, including: acquiring the variance of the channel noise superimposed on the channel between terminal A1 in cell A and access network device A, acquiring the variance of the channel noise superimposed on the channel between terminal A2 in cell A and access network device A, acquiring the variance of the channel noise superimposed on the channel between terminal B1 in cell B and access network device A, acquiring the variance of the channel noise superimposed on the channel between terminal B2 in cell B and access network device A, acquiring the variance of the channel noise superimposed on the channel between terminal C1 in cell C and access network device A, and acquiring the variance of the channel noise superimposed on the channel between terminal C2 in cell C and access network device A.

[0184] Similarly, access network device B will also obtain the variance of the channel noise superimposed on the channel between each terminal in cell A, cell B, and cell C and access network device B. Access network device C will also obtain the variance of the channel noise superimposed on the channel between each terminal in cell A, cell B, and cell C and access network device C.

[0185] For example, the access network device A obtains the variance of the channel noise superimposed on the channel between the terminal A1 of the cell A and the access network device A.

[0186] In some embodiments, the terminal A1 of the cell A sends the variance of the channel noise superimposed on the channel between the terminal A1 and the access network device A to the access network device A. For example, the access network device A sends a pilot signal to the terminal A1 in step 1 of step S502. After receiving the pilot signal from the access network device A, the terminal A1 can calculate the variance of the channel noise superimposed on the channel between the terminal A1 and the access network device A by the difference between the received power of the pilot signal and the known transmission power, and the channel gain, and send the variance of the channel noise superimposed on the channel between the terminal A1 and the access network device A to the access network device A.

[0187] In this case, the variance of the channel noise superimposed on the channel between the terminal A1 of the cell A and the access network device A can be obtained in step S502.

[0188] It can be understood that for the terminals in the cell B and the cell C, after receiving the downlink pilot signal sent by the access network device A, the variance of the channel noise is calculated by the same method as described above, and then uploaded to the access network device B or the access network device C in the cell. The access network device A, the access network device B and the access network device C share these variance values through the central unit connected by wire.

[0189] According to the above method, the access network device A can obtain the variance of the channel noise superimposed on the channel between the terminal and the access network device A sent by each terminal in the cell A, the cell B and the cell C, and sum them up, denoted as the additive white Gaussian noise vector received by the access network device A , the mean is , and the covariance matrix is . Here, the sum of the variances of the channel noise is

[0190] It can be understood that the access network device B also obtains the variance of the channel noise superimposed on the channel between the terminal and the access network device B in the cell A, the cell B and the cell C, and sums them up, denoted as the additive white Gaussian noise vector received by the access network device B , the mean is , and the covariance matrix is . Here, the sum of the variances of the channel noise is​ i.e. the sum of the variances of the channel noise as mentioned above.

[0191] It can be understood that the access network device C also acquires the variances of the channel noise superimposed on the channels between each terminal in the cell A, the cell B and the cell C and the access network device C, and sums them up, denoted as the additive white Gaussian noise vector superimposed on the channel received by the access network device C , the mean of which is , and the covariance matrix is . Herein, the i.e. the sum of the variances of the channel noise as mentioned above. Without loss of generality, the method embodiment assumes that the power levels of the channel noise of the cell A, the cell B and the cell C are consistent, so the variances of the channel noise received by the access network devices of the respective cells are the same, all being .

[0192] The access network device A acquires the variances of the channel estimation errors between each terminal in the cell A, the cell B and the cell C and the access network device A, including: acquiring the variance of the channel estimation error between the terminal A1 of the cell A and the access network device A, acquiring the variance of the channel estimation error between the terminal A2 of the cell A and the access network device A, acquiring the variance of the channel estimation error between the terminal B1 of the cell B and the access network device A, acquiring the variance of the channel estimation error between the terminal B2 of the cell B and the access network device A, acquiring the variance of the channel estimation error between the terminal C1 of the cell C and the access network device A, and acquiring the variance of the channel estimation error between the terminal C2 of the cell C and the access network device A.

[0193] The variance of the channel estimation error is related to the channel error matrix, which is the difference between the actual channel matrix and the channel estimation matrix. Since the actual channel is unknown, the channel error matrix cannot be directly calculated, but the actual channel can be assumed to be a Rayleigh fading channel, and the variance of the channel estimation error is described.

[0194] For example, the Rayleigh fading channel matrix of the terminal A1 of the cell A to the access network device A is , , denoting the channel error matrix of the terminal A1 of the cell A to the access network device A; the Rayleigh fading channel matrix of the terminal A2 of the cell A to the access network device A is , , denoting the channel error matrix of the terminal A2 of the cell A to the access network device A; the Rayleigh fading channel matrix of the terminal B1 of the cell B to the access network device A is , , HAB1is the channel error matrix from terminal B1 of cell B to access network device A; the Rayleigh fading channel matrix from terminal B2 of cell B to access network device A is , , HAB2is the channel error matrix from terminal B2 of cell B to access network device A; the Rayleigh fading channel matrix from terminal C1 of cell C to access network device A is , , HAC1is the channel error matrix from terminal C1 of cell C to access network device A; the Rayleigh fading channel matrix from terminal C2 of cell C to access network device A is , , HAC2is the channel error matrix from terminal C2 of cell C to access network device A. Wherein, the Rayleigh fading channel matrix is an M x M matrix, and all the channel error matrices are M x M matrices.

[0195] Suppose the channel error matrix obeys a complex Gaussian distribution with zero mean, such as satisfies ~ wherein, represents stacking into a column vector by column, represents a complex Gaussian distribution vector with mean vector and covariance matrix . is the variance of the channel estimation error.

[0196] In some embodiments, the variance of the channel estimation error between terminal A1 of cell A and access network device A is sent by terminal A1 to access network device A. Exemplarily, in step 1 of step S502, access network device A sends a pilot signal to terminal A1, and accordingly, after terminal A1 receives the pilot signal from access network device A, the terminal can calculate the channel residual error between terminal A1 and access network device A according to the received pilot signal and the local pilot signal, combined with the channel estimation gain, and the sum of squares of a large number of residual errors can calculate the variance of the channel estimation error , and terminal A1 sends the variance of the channel estimation error between itself and access network device A to access network device A.

[0197] In this case, the acquisition of the variance of the channel estimation error between each terminal of cell A, cell B and cell C and access network device A in step S605 can be completed in step S502.

[0198] For the terminals in cell B and cell C, after receiving the downlink pilot signal sent by the access network device A, the variance of the channel estimation error is calculated by using the same method as described above, and then the variance is uploaded to the access network device B or the access network device C in the cell. The access network device A, the access network device B and the access network device C will share these variance values through the central unit connected by wire.

[0199] According to the above method, the access network device A can obtain the variance of the channel estimation error between each terminal in cell A, cell B and cell C and the access network device A . The access network device B also obtains the variance of the channel estimation error between each terminal in cell A, cell B and cell C and the access network device B . The access network device C also obtains the variance of the channel estimation error between each terminal in cell A, cell B and cell C and the access network device C Without loss of generality, the embodiments of the present application assume that the power levels of the channel estimation errors of cell A, cell B and cell C are consistent, so the variances of the channel estimation errors between the access network devices of each cell and each terminal are the same, which are .

[0200] It should be noted that the equivalent channel matrix between each terminal in cell A, cell B and cell C and the access network device A, the variance of the channel noise superimposed in the channel between each terminal in cell A, cell B and cell C and the access network device A, and the variance of the channel estimation error between each terminal in cell A, cell B and cell C and the access network device A are unchanged in each round.

[0201] S606, the access network device A calculates the first round decoding matrix of cell A based on the first precoding matrix of cell A, cell B and cell C, the second precoding matrix of each terminal in cell A, cell B and cell C, the equivalent channel matrix between each terminal in cell A, cell B and cell C and the access network device A, the variance of the channel noise superimposed in the channel between each terminal in cell A, cell B and cell C and the access network device A, and the variance of the channel estimation error between each terminal in cell A, cell B and cell C and the access network device A.

[0202] Wherein, the formula (1) for calculating the t-th round decoding matrix of the i-th cell is as follows, i is sequentially taken in {1, 2, 3}, and t is sequentially taken in {1, 2, …, N}.

[0203] Formula (1),

[0204] Wherein, denotes the equivalent channel matrix between the kth terminal in the jth cell and the access network device in the ith cell, denotes the first precoding matrix of the tth round in the jth cell, denotes the conjugate transpose of the first precoding matrix of the tth round in the jth cell, denotes the conjugate transpose of the equivalent channel matrix between the kth terminal in the jth cell and the access network device in the ith cell, denotes the variance of the channel estimation error between the kth terminal in the jth cell and the access network device in the ith cell, denotes the trace of the matrix in the parentheses, denotes the second precoding matrix of the kth terminal in the jth cell, denotes the conjugate matrix of the second precoding matrix of the kth terminal in the jth cell, denotes the variance of the additive white Gaussian noise vector superimposed in the channel, denotes the identity matrix, denotes the equivalent channel matrix between the kth terminal in the ith cell and the access network device in the ith cell, denotes the first precoding matrix of the tth round in the ith cell.

[0205] That is, the calculation of the tth round decoding matrix of the ith cell not only refers to the first precoding matrix of the tth round of each terminal in the ith cell, but also refers to the first precoding matrix of the tth round of each terminal in other cells, and the second precoding matrix of each terminal in multiple cells. Therefore, the access network device in the ith cell can gradually correct the error of the decoding matrix obtained in the last round through the tth round decoding matrix calculated by multiple rounds, so that the decoding result obtained by the access network device in the ith cell using the finally obtained decoding matrix of the access network device in the ith cell is closer to the target received signal, and the decoding accuracy is improved.

[0206] The derivation process of formula (1) for the access network device in the ith cell to calculate the decoding matrix of the ith cell can be referred to the following description.

[0207] When t = 1, formula (1) is the formula for the access network device in the ith cell to calculate the 1st round decoding matrix of the ith cell.

[0208] For example, the access network device A calculates the first round decoding matrix of cell A based on the first round first precoding matrix of cell A, cell B and cell C, the second precoding matrix of each terminal in cell A, cell B and cell C, the equivalent channel matrix between each terminal in cell A, cell B and cell C and the access network device A, the variance of the channel noise superimposed in the channel between each terminal in cell A, cell B and cell C and the access network device A, and the variance of the channel estimation error between each terminal in cell A, cell B and cell C and the access network device A. The result is shown in equation (2).

[0209] Equation (2),

[0210] It can be understood that the access network device B can also calculate the first round decoding matrix of cell B based on the first round first precoding matrix of cell A, cell B and cell C, the second precoding matrix of each terminal in cell A, cell B and cell C, the equivalent channel matrix between each terminal in cell A, cell B and cell C and the access network device B, the variance of the channel noise superimposed in the channel between each terminal in cell A, cell B and cell C and the access network device B, and the variance of the channel estimation error between each terminal in cell A, cell B and cell C and the access network device B. The result is shown in equation (3).

[0211] Equation (3),

[0212] The access network device C can also calculate the first round decoding matrix of cell C based on the first round first precoding matrix of cell A, cell B and cell C, the second precoding matrix of each terminal in cell A, cell B and cell C, the equivalent channel matrix between each terminal in cell A, cell B and cell C and the access network device C, the variance of the channel noise superimposed in the channel between each terminal in cell A, cell B and cell C and the access network device C, and the variance of the channel estimation error between each terminal in cell A, cell B and cell C and the access network device C. The result is shown in equation (4).

[0213] Equation (4),

[0214] The following takes the terminal A1 interacting with multiple access network devices to obtain the second round first precoding matrix of cell A as an example to introduce the method of the embodiments of the present application.

[0215] As Figure 7As shown, the above procedure (3), i.e., the "2nd round precoding matrix determination procedure", can include S701-S706. Since the access network device A, the access network device B and the access network device C are all connected to the center unit through wires, after they each calculate the decoding matrix of the cell where they are located, they will share the decoding matrix through the center unit.

[0216] S701, the access network device A sends the 1st round decoding matrix of the cell A, the cell B and the cell C to the terminal A1 and the terminal A2.

[0217] S702, the access network device B sends the 1st round decoding matrix of the cell A, the cell B and the cell C to the terminal B1 and the terminal B2.

[0218] S703, the access network device C sends the 1st round decoding matrix of the cell A, the cell B and the cell C to the terminal C1 and the terminal C2.

[0219] S704, the terminal A1 receives the 1st round decoding matrix of the cell A, the cell B and the cell C.

[0220] It can be understood that the terminal A2, the terminal B1, the terminal B2, the terminal C1 and the terminal C2 will also receive the 1st round decoding matrix of the cell A, the cell B and the cell C.

[0221] S705, the terminal A1 obtains the 2nd precoding matrix of each terminal in the cell A, the equivalent channel matrix of the terminal A1 and the terminal A2 to the access network device A, the access network device B and the access network device C in the cell A, the variance of the channel estimation error between each terminal and the access network device A in the cell A, the cell B and the cell C, and a plurality of Lagrange multipliers.

[0222] In step S605, the access network device of each cell shares the 2nd precoding matrix of each terminal and other information, so that each terminal will be able to obtain the information of the 2nd precoding matrix of the remaining terminals by broadcasting these information by each access network device to each terminal in the cell.

[0223] For example, the access network device A sends the 2nd precoding matrix of each terminal to the terminal A1 and the terminal A2, so that the terminal A1 and the terminal A2 can obtain the 2nd precoding matrix of all terminals in the cell A.

[0224] Similarly, each terminal in the cell B can obtain the 2nd precoding matrix of all terminals in the cell B, and each terminal in the cell C can obtain the 2nd precoding matrix of all terminals in the cell C.

[0225] The terminal A1 obtains the equivalent channel matrix of the terminal A1 and the terminal A2 to the access network device A, the access network device B and the access network device C in the cell A, comprising: obtaining the equivalent channel matrix of the terminal A1 to the access network device A in the cell A , obtaining the equivalent channel matrix of the terminal A2 to the access network device A in the cell A , obtaining the equivalent channel matrix of the terminal A1 to the access network device B in the cell A , obtaining the equivalent channel matrix of the terminal A2 to the access network device B in the cell A , obtaining the equivalent channel matrix of the terminal A1 to the access network device C in the cell A , obtaining the equivalent channel matrix of the terminal A2 to the access network device C in the cell A .

[0226] Wherein, , is the channel estimation matrix between the terminal A1 and the access network device A in the cell A; , is the channel estimation matrix between the terminal A2 and the access network device A in the cell A; , is the channel estimation matrix between the terminal A1 and the access network device B in the cell A; , is the channel estimation matrix between the terminal A2 and the access network device B in the cell A; , is the channel estimation matrix between the terminal A1 and the access network device C in the cell A; , is the channel estimation matrix between the terminal A2 and the access network device C in the cell A, all terminals and all access network devices are configured with M antennas, and the above equivalent channel matrix and channel estimation matrix are MxM matrices.

[0227] It should be noted that in the block fading channel, it can be considered that the channel is unchanged within a time block, that is, the channel estimation matrix and the variance of the channel estimation error are also unchanged. In addition, the channel is reciprocal, and the uplink channel and the downlink channel are the same, so the channel estimation matrix, the equivalent channel matrix and the variance of the channel estimation error obtained by the downlink channel estimation in S605 can be directly used in S705. Meanwhile, in S605, the terminal uploads these estimation quantities to the access network device in the cell where the terminal is located, and the access network devices share these quantities through the wired connection center unit, so the access network devices in each cell can directly issue these information to the terminals in the cell.

[0228] For example, by step S605, the access network device A obtains the equivalent channel matrix and the variance of channel estimation error between the terminal A1, the terminal A2, the terminal B1, the terminal B2, the terminal C1, the terminal C2 and the access network device A, the access network device B, the access network device C respectively, and then the access network device A can send the equivalent channel matrix and the variance of channel estimation error between the terminal A1, the terminal A2, the terminal B1, the terminal B2, the terminal C1, the terminal C2 and the access network device A, the access network device B, the access network device C respectively to the terminal A1 in step S705. That is, in this way, the terminal A1 can obtain the equivalent channel matrix between the terminal A1 and the terminal A2 to the access network device A, the access network device B and the access network device C respectively and the variance of channel estimation error between each terminal and the access network device A in the cell A, the cell B and the cell C.

[0229] Similarly, the terminal B1 can obtain the equivalent channel matrix between the terminal B1 and the terminal B2 to the access network device A, the access network device B and the access network device C respectively and the variance of channel estimation error between each terminal and the access network device B in the cell A, the cell B and the cell C.

[0230] The terminal C1 can obtain the equivalent channel matrix between the terminal C1 and the terminal C2 to the access network device A, the access network device B and the access network device C respectively and the variance of channel estimation error between each terminal and the access network device C in the cell A, the cell B and the cell C.

[0231] Wherein, the terminal A1 obtains the plurality of Lagrange multipliers comprises: the terminal A1 obtains the Lagrange multiplier of the cell A , the Lagrange multiplier of the cell B , the Lagrange multiplier of the cell C .

[0232] Wherein, the Lagrange multiplier of the jth cell is calculated by using the bisection method or the Newton iteration method to solve the following equation.

[0233]

[0234] In the equation, = ,

[0235] .

[0236] The derivation process of the equation for calculating the Lagrange multiplier of the jth cell can be referred to the following description.

[0237] It should be noted that the equivalent channel matrix of terminal A1 and terminal A2 in cell A to access network device A, access network device B and access network device C, the variance of channel estimation error of terminal A1 and terminal A2 in cell A to access network device A, access network device B and access network device C, and the plurality of Lagrange multipliers are all unchanged.

[0238] S706, terminal A1 calculates the second round first precoding matrix of cell A based on the first round decoding matrix of cell A, cell B and cell C, the second precoding matrix of each terminal in cell A, the equivalent channel matrix of terminal A1 and terminal A2 in cell A to access network device A, access network device B and access network device C, the variance of channel estimation error between each terminal in cell A, cell B and cell C and access network device A, and the plurality of Lagrange multipliers.

[0239] Wherein, the formula (5) of the terminal of the jth cell calculating the rth round first precoding matrix of the jth cell is as follows, j is sequentially taken in {1, 2, 3}, and r is sequentially taken in {2, 3……N}.

[0240] Formula (5),

[0241] Wherein, Hjk,i represents the equivalent channel matrix between the kth terminal of the jth cell and the access network device of the ith cell, , Hjk,i represents the channel estimation matrix between the kth terminal of the jth cell and the access network device of the ith cell, Wjk represents the second precoding matrix of the kth terminal of the jth cell, Hjk,i represents the conjugate transpose of the equivalent channel matrix between the kth terminal of the jth cell and the access network device of the ith cell, Dik represents the decoding matrix of the ith cell in the r-1th round, Dik represents the conjugate transpose of the decoding matrix of the ith cell in the r-1th round, σjk,i represents the variance of the channel estimation error between the kth terminal of the jth cell and the access network device of the ith cell, tr(·) represents the trace of the matrix in the parentheses, Wjk represents the conjugate matrix of the second precoding matrix of the kth terminal of the jth cell, λjk represents the Lagrange multiplier of the jth cell, I represents the unit matrix, Hjk,j represents the conjugate transpose of the equivalent channel matrix between the kth terminal of the jth cell and the access network device of the jth cell, Djk represents the decoding matrix of the jth cell in the r-1th round.

[0242] That is, the calculation of the first precoding matrix of the rth round of the jth cell refers to the decoding matrix of the (r-1)th round of the jth cell. Therefore, the terminal in the jth cell can gradually correct the error of the first precoding matrix obtained in the last round through multiple rounds of calculation of the first precoding matrix, so that the precoding matrix (including the first precoding matrix and the second precoding matrix) of the terminal in the jth cell finally obtained by the terminal in the jth cell can better match the decoding requirements of the receiving end, more accurately adapt to the current channel state, and optimize the signal transmission performance.

[0243] The formula (5) for the terminal of the jth cell to calculate the first precoding matrix of the jth cell can be derived with reference to the following description.

[0244] When r=2, the formula (5) is the formula for the terminal of the jth cell to calculate the first precoding matrix of the 2nd round of the jth cell.

[0245] For example, the terminal A1 calculates the second precoding matrix of the 2nd round of the cell A based on the decoding matrix of the 1st round of the cell A, the cell B and the cell C, the second precoding matrix of each terminal in the cell A, the equivalent channel matrix of the terminal A1 and the terminal A2 to the access network device A, the access network device B and the access network device C respectively in the cell A, the variance of the channel estimation error between each terminal and the access network device A in the cell A, the cell B and the cell C, and a plurality of Lagrange multipliers. The result is shown in formula (6).

[0246] The formula (6),

[0247] It can be understood that the terminal A2 calculates the second precoding matrix of the 2nd round of the cell A based on the decoding matrix of the 1st round of the cell A, the cell B and the cell C, the second precoding matrix of each terminal in the cell A, the equivalent channel matrix of the terminal A1 and the terminal A2 to the access network device A, the access network device B and the access network device C respectively in the cell A, the variance of the channel estimation error between each terminal and the access network device A in the cell A, the cell B and the cell C, and a plurality of Lagrange multipliers. The result is shown in formula (6).

[0248] The terminal B1 and the terminal B2 calculate the second precoding matrix of the 2nd round of the cell B based on the decoding matrix of the 1st round of the cell A, the cell B and the cell C, the second precoding matrix of each terminal in the cell B, the equivalent channel matrix of the terminal B1 and the terminal B2 to the access network device A, the access network device B and the access network device C respectively in the cell B, the variance of the channel estimation error between each terminal and the access network device B in the cell A, the cell B and the cell C, and a plurality of Lagrange multipliers. The result is shown in formula (7).

[0249] Equation (7),

[0250] The terminal C1 and the terminal C2 calculate the second round first precoding matrix of the cell C based on the first round decoding matrix of the cell A, the cell B and the cell C, the second precoding matrix of each terminal in the cell C, the equivalent channel matrix of the terminal C1 and the terminal C2 to the access network device A, the access network device B and the access network device C respectively in the cell C, the variance of the channel estimation error between each terminal and the access network device C in the cell A, the cell B and the cell C, and the plurality of Lagrange multipliers. The result is shown in Equation (8).

[0251] Equation (8),

[0252] The following takes the access network device A interacting with the terminals of the plurality of cells to obtain the second round decoding matrix of the cell A as an example to introduce the method of the embodiments of the present application.

[0253] As shown in Equation (4), the above process (4), that is, the second round decoding matrix determination process, can include S801-S803. Figure 8

[0254] S801, any terminal in the cell (such as the terminal A1 or the terminal A2 in the cell A, the terminal B1 or the terminal B2 in the cell B, or the terminal C1 or the terminal C2 in the cell C) sends the second round first precoding matrix of the corresponding cell to the access network device of the corresponding cell.

[0255] For example, the terminal A1 of the cell A sends the second round first precoding matrix of the cell A to the access network device A. Or, the terminal A2 of the cell A sends the second round first precoding matrix of the cell A to the access network device A.

[0256] Similarly, the terminal B1 of the cell B sends the second round first precoding matrix of the cell B to the access network device B. Or, the terminal B2 of the cell B sends the second round first precoding matrix of the cell B to the access network device B.

[0257] The terminal C1 of the cell C sends the second round first precoding matrix of the cell C to the access network device C. Or, the terminal C2 of the cell C sends the second round first precoding matrix of the cell C to the access network device C.

[0258] S802, the access network device A receives the second round first precoding matrix of the cell A, the cell B and the cell C. ​​​​

[0259] As mentioned above, each access network device shares the first precoding matrix of the second round of each cell through the central unit of the wired connection. Therefore, in addition to the access network device A, the access network device B and the access network device C will also receive the first precoding matrix of the second round of the cell A, the cell B and the cell C.

[0260] S803, the access network device A calculates the decoding matrix of the second round of the cell A based on the first precoding matrix of the second round of the cell A, the cell B and the cell C, the second precoding matrix of each terminal in the cell A, the cell B and the cell C, the equivalent channel matrix between each terminal in the cell A, the cell B and the cell C and the access network device A, the variance of the channel noise superimposed in the channel between each terminal in the cell A, the cell B and the cell C and the access network device A, and the variance of the channel estimation error between each terminal in the cell A, the cell B and the cell C and the access network device A.

[0261] The second precoding matrix of each terminal in the cell A, the cell B and the cell C is unchanged in each round, and the access network device A can obtain the second precoding matrix of each terminal in the cell A, the cell B and the cell C through the above step S604.

[0262] The equivalent channel matrix between each terminal in the cell A, the cell B and the cell C and the access network device A, the variance of the channel noise superimposed in the channel between each terminal in the cell A, the cell B and the cell C and the access network device A, and the variance of the channel estimation error between each terminal in the cell A, the cell B and the cell C and the access network device A are unchanged in each round, and the access network device A can obtain these data through the above step S605. The data obtained through the step S605 can be used.

[0263] When t = 2, the formula (1) is the formula for the access network device of the ith cell to calculate the decoding matrix of the second round of the ith cell.

[0264] For example, the access network device A calculates the decoding matrix of the second round of the cell A , and the result is shown in the formula (2). The access network device B calculates the decoding matrix of the second round of the cell B , and the result is shown in the formula (3). The access network device C calculates the decoding matrix of the second round of the cell C , and the result is shown in the formula (4).

[0265] The difference is that, wherein, W2A represents the first precoding matrix of the second round of the cell A, W2B represents the first precoding matrix of the second round of the cell B, W2C represents the first precoding matrix of the second round of the cell C, denotes the conjugate transpose of the first precoding matrix of the 2nd round of cell A, denotes the conjugate transpose of the first precoding matrix of the 2nd round of cell B, denotes the conjugate transpose of the first precoding matrix of the 2nd round of cell C.

[0266] The following takes the terminal A1 interacting with multiple access network devices to obtain the first precoding matrix of the 3rd round of cell A as an example to introduce the method of the embodiments of the present application.

[0267] As shown in the above flow (5), i.e., the "3rd round precoding matrix determination flow", it can include S901-S905. As described before, since the access network device A, the access network device B and the access network device C are all connected to the center unit through wires, after they each calculate the decoding matrix of the cell where they are located, they will share these decoding matrices through the center unit. Figure 9 S901, the access network device A sends the 2nd round decoding matrix of cell A, cell B and cell C to the terminal A1 and the terminal A2.

[0268] S902, the access network device B sends the 2nd round decoding matrix of cell A, cell B and cell C to the terminal B1 and the terminal B2.

[0269] S903, the access network device C sends the 2nd round decoding matrix of cell A, cell B and cell C to the terminal C1 and the terminal C2.

[0270] S904, the terminal A1 receives the 2nd round decoding matrix of cell A, cell B and cell C.

[0271] It can be understood that the terminal A2, the terminal B1, the terminal B2, the terminal C1 and the terminal C2 will also receive the 2nd round decoding matrix of cell A, cell B and cell C.

[0272] S905, the terminal A1 calculates the first precoding matrix of the 3rd round of cell A based on the 2nd round decoding matrix of cell A, cell B and cell C, the second precoding matrix of each terminal in cell A, the equivalent channel matrix of the terminal A1 and the terminal A2 in cell A to the access network device A, the access network device B and the access network device C, the variance of the channel estimation error between each terminal in cell A, cell B and cell C and the access network device A, and multiple Lagrange multipliers.

[0273]

[0274] ​Wherein, the second precoding matrix of each terminal in cell A, the equivalent channel matrix of terminal A1 and terminal A2 in cell A to access network device A, access network device B and access network device C respectively, the variance of the channel estimation error between each terminal in cell A, cell B and cell C and access network device A, and the plurality of Lagrange multipliers are unchanged in each round, and terminal A1 can obtain these data through step S705.

[0275] When r=3, formula (5) is the formula for terminal of the jth cell to calculate the third round first precoding matrix of the jth cell.

[0276] For example, the terminal (terminal A1 and / or terminal A2) of cell A calculates the third round first precoding matrix of cell A , and the result is shown in formula (6). The terminal (terminal B1 and / or terminal B2) of cell B calculates the third round first precoding matrix of cell B , and the result is shown in formula (7). The terminal (terminal C1 and / or terminal C2) of cell C calculates the third round first precoding matrix of cell C , and the result is shown in formula (8).

[0277] Different from the above, wherein, denotes the second round decoding matrix of cell A, denotes the second round decoding matrix of cell B, denotes the second round decoding matrix of cell C, denotes the conjugate transpose of the second round decoding matrix of cell A, denotes the conjugate transpose of the second round decoding matrix of cell B, denotes the conjugate transpose of the second round decoding matrix of cell C.

[0278] It should be noted that the access network device A interacts with the terminals of the plurality of cells to obtain the method of the qth round decoding matrix of cell A, which can refer to the method of obtaining the second round decoding matrix of cell A by access network device A in S801-S803, and the present application embodiment will not be repeated here. Wherein, q is sequentially taken in {3, 4……N}. Through N rounds of interaction, the access network device A can continuously adjust the decoding matrix according to the optimization result of the precoding matrix, so as to more accurately decode the received signal and improve the accuracy of decoding.

[0279] The terminal A1 interacts with the plurality of access network devices to obtain the method of the pth round of the first precoding matrix of the cell A. The method can refer to the method of the terminal A1 obtaining the third round of the precoding matrix in S901-S905, and details are not described herein. The p is sequentially taken in {4, 5,..., N}. Through the N rounds of interaction, the terminal A1 can continuously adjust the precoding matrix according to the optimization result of the decoding matrix to maximize the signal transmission performance of the system, thereby better adapting to the complex channel state information, reducing the influence of the channel correlation, and thereby enhancing the signal transmission quality.

[0280] For example, when N is 300, the first precoding matrix of the cell A and the decoding matrix are alternately iteratively calculated, and after 300 rounds of interaction, the terminal A1 of the cell A obtains the 300th round of the precoding matrix of the cell A, and the access network device A obtains the 300th round of the decoding matrix of the cell A. The 300th round of the precoding matrix of the terminal A1 of the cell A includes the 300th round of the first precoding matrix of the cell A and the second precoding matrix of the terminal A1.

[0281] According to the method of the embodiment of the present application, each round of the precoding matrix (including the first precoding matrix and the second precoding matrix) calculated by the first terminal is calculated according to the optimization result of the last round of the decoding matrix, so that the error of the precoding matrix calculated by the first terminal in the last round can be gradually corrected. Moreover, the calculation of the n+1th round of the precoding matrix of the first cell not only refers to the nth round of the decoding matrix of the first cell, but also refers to the nth round of the decoding matrix of the cells other than the first cell. Therefore, after N rounds of interaction, the Nth round of the precoding matrix obtained finally can better match the decoding requirement of the receiving end, more accurately adapt to the current channel state, and optimize the signal transmission performance. At the same time, the first terminal uses such a precoding matrix to align the uplink interference signals of other cells, which facilitates the first access network device to better separate the target receiving signal and the interference signal.

[0282] By the method of the embodiment of the present application, the decoding matrix calculated by the first access network device in each round is calculated according to the optimization result of the precoding matrix in the round, so that the error of the decoding matrix calculated by the first access network device in the last round can be corrected step by step. Moreover, the first access network device calculates the decoding matrix of the first cell in the n th round, which not only refers to the n th precoding matrix (including the first precoding matrix and the second precoding matrix) of each terminal in the first cell, but also refers to the n th precoding matrix of each terminal in the other cells except the first cell. Therefore, after N rounds of interaction, the decoding matrix obtained in the N th round can more accurately decode the uplink signal received by the first access network device, and the accuracy of the received signal of the first access network device is improved. At the same time, the first access network device uses such a decoding matrix, which can minimize the interference signal received by the first access network device from the other cells except the first cell, minimize the error caused by the channel estimation error during signal transmission, and minimize the channel noise during signal transmission, thereby improving the accuracy of uplink signal transmission of terminals in each cell.

[0283] For example, the specific implementation process of determining the coding and decoding matrix is shown in Table 1.

[0284] Table 1

[0285]

[0286] The method provided by the present application can not only be applied to an air computing system of two cells, but also be applied to an air computing system of three or more cells. After N rounds of alternating iteration, the first access network device can calculate the decoding matrix obtained in the N th round, and the first terminal can calculate the precoding matrix obtained in the N th round (including the first precoding matrix and the second precoding matrix). The optimization results of the precoding matrix and the decoding matrix tend to be globally optimal. The precoding matrix and the decoding matrix can better cooperate with each other, the first precoding matrix obtained finally can align the interference signals from other cells, the second precoding matrix obtained finally can align the signals sent by the terminals in each cell to the access network device of the cell, and the decoding matrix obtained finally can minimize the interference, channel estimation error and noise in the signals received by the access network device of the cell, thereby improving the transmission rate and reliability of the entire communication system.

[0287] The above is an example of calculating the first precoding matrix and the decoding matrix of cell A in an AirComp system with three cells. In fact, the AirComp system can have multiple cells, and the precoding matrix of each terminal in the multiple cells and the decoding matrix of the multiple cells can be calculated according to the above calculation process.

[0288] The following describes the derivation process of formula (1) for calculating the decoding matrix of cell i in step S606, the derivation process of formula (5) for calculating the first precoding matrix of cell j in step S706, and the derivation process of the equation for calculating the Lagrange multiplier of cell j in step S705.

[0289] For example, the embodiments of this application use Figure 2 The three cells shown are constructed using the access network equipment and terminals as examples. Figure 11 Taking the three-cell over-the-air computing system analysis block diagram shown as an example, this application introduces the formulas for obtaining the precoding matrix and decoding matrix, and the method for obtaining the Lagrange multiplier equations provided in the embodiments. Figure 10 As shown, it includes steps S1001-S1003.

[0290] S1001, In the AirComp system, the access network equipment of each cell calculates the uplink data it actually receives (i.e., the air calculation result).

[0291] The following description will be based on the uplink data actually received by access network device A in cell A.

[0292] For example, the three-cell over-the-air computing system analysis block diagram includes uplink data sent by terminal A1 (also known as the first terminal) in cell A (also known as the first cell). Uplink data sent by terminal A2 (also known as the second terminal) in cell A Uplink data sent by terminal B1 (also known as the first terminal) in cell B (also known as the second cell). Uplink data sent by terminal B2 (also known as the second terminal) in cell B. Uplink data sent by terminal C1 (also known as the first terminal) in cell C (also known as the third cell). Uplink data sent by terminal C2 (also known as the second terminal) in cell C. .

[0293] in, , This represents the expected value of the data within the curly braces. Represents the identity matrix. This represents the uplink data sent by the k-th terminal in the i-th cell. express The conjugate transpose of , i=1,2,3; k=1,2. When i≠j, , This represents the uplink data sent by the k-th terminal in the j-th cell. express The conjugate transpose of . denote zero matrix, i = 1, 2, 3; j = 1, 2, 3; k = 1, 2.

[0294] The terminal A1, the terminal A2, the terminal B1, the terminal B2, the terminal C1 and the terminal C2 are all configured with M root antennas, and the uplink data transmitted by each terminal to the access network device A is multi-flow data, which includes d data flows, that is, , , , , , .

[0295] The uplink data sent by each terminal is encoded into uplink signals after the pre-coding matrix, and is sent to the access network device A through the M root antennas. After the uplink signals are transmitted through the channel, the access network device A decodes the received uplink signal superposition result through the decoding matrix to obtain the final air computing result. Then, the uplink signal received by the access network device A after the process is denoted as formula (9).

[0296] Formula (9),

[0297] Substituting , , , , , , the uplink signal received by the access network device A is Further denoted as formula (10).

[0298] Formula (10),

[0299] The decoding matrix of the cell A is , and the uplink data (i.e. the air computing result) of the access network device A after decoding through the decoding matrix is formula (11).

[0300] Formula (11),

[0301] In the uplink signal transmission process, the most ideal case is that the transmitted data is the same as the received data, that is, the target uplink data of the access network device A is .

[0302] Through the above derivation, the target uplink data of the access network device A and the actual uplink data (i.e. the air computing result) can be obtained.

[0303] Understandably, an actual AirComp system contains multiple cells. Taking the number of cells as Ku and the number of terminals in each cell as Ka as an example, we can obtain the destination uplink data and actual uplink data of the access network devices in each cell.

[0304] The uplink data sent by the k-th terminal in the i-th cell is ,and .in, This represents the expected value of the data within the curly braces. Represents the identity matrix. express The conjugate transpose of , i=1,2,……,Ku, k=1,2,……,Ka.

[0305] The uplink data sent by the k-th terminal in the j-th cell is When i≠j , express The conjugate transpose of . Let denote the zero matrix, j=1,2,……,Ku, k=1,2,……,Ka.

[0306] The precoding matrix of the k-th terminal in the i-th cell Including the first precoding matrix of the i-th cell The second precoding matrix of the i-th cell and the k-th terminal , , i=1,2,…,Ku, k=1,2,…,Ka. This is used to align uplink interference data received by the access network device in cell i from other cells among multiple cells excluding cell i. It can also be understood as the first precoding matrix of each terminal in the i-th cell, because the first precoding matrix of all terminals in the i-th cell is the same. Used to align uplink data sent by the k-th terminal in the i-th cell to the access network device in the i-th cell, and , It is the channel estimation matrix between the k-th terminal in the i-th cell and the access network equipment in the i-th cell, i=1,2,……,Ku, k=1,2,……,Ka.

[0307] The precoding matrix of the k-th terminal in the j-th cell Including the first precoding matrix of the j-th cell The second precoding matrix of the j-th cell and the k-th terminal , , j=1,2,…,Ku, k=1,2,…,Ka. aligning uplink data transmitted by the kth terminal in the ith cell to the access network device in the ith cell, and The first precoding matrix of the jth cell can also be understood as the first precoding matrix of each terminal in the jth cell. aligning uplink data transmitted by the kth terminal in the jth cell to the access network device in the jth cell, and , is the channel estimation matrix between the kth terminal in the jth cell and the access network device in the jth cell, j = 1, 2, …, Ku, k = 1, 2, …, Ka.

[0308] The uplink data transmitted by the kth terminal in the ith cell is a d × 1 matrix, that is, The precoding matrix of the kth terminal in the ith cell is a M × d matrix, that is, The first precoding matrix of the ith cell is a M × d matrix, that is, The second precoding matrix of the kth terminal in the ith cell is a M × M matrix, that is, .

[0309] The uplink data transmitted by the kth terminal in the jth cell is a d × 1 matrix, that is, The precoding matrix of the kth terminal in the jth cell is a M × d matrix, that is, The first precoding matrix of the jth cell is a M × d matrix, that is, The second precoding matrix of the kth terminal in the jth cell is a M × M matrix, that is, .

[0310] The Rayleigh fading channel matrix from the kth terminal in the ith cell to the access network device in the ith cell is , i = 1, 2, …, Ku, k = 1, …, Ka. , is the channel estimation matrix from the kth terminal in the ith cell to the ith cell, is the channel error matrix from the kth terminal in the ith cell to the ith cell.

[0311] The Rayleigh fading channel matrix from the kth terminal in the jth cell to the access network device in the ith cell is , where j = 1, 2, …, Ku, k = 1, …, Ka. , is the channel estimation matrix from the kth terminal in the jth cell to the ith cell, is the channel error matrix from the kth terminal in the jth cell to the ith cell. And satisfies ~ wherein, denotes the stacked into a column vector, denotes the mean vector , and the covariance matrix of the complex Gaussian distribution vector is called the variance of the channel estimation error.

[0312] Suppose each access network device in each cell has M antennas, i.e., the access network device receives the uplink signal through M antennas, and the Rayleigh fading channel matrix from the kth terminal in the jth cell to the access network device in the ith cell is an M x M matrix, i.e. The channel estimation matrix from the kth terminal in the jth cell to the access network device in the ith cell is an M x M matrix, i.e. The channel error matrix from the kth terminal in the jth cell to the access network device in the ith cell is an M x M matrix, i.e. .

[0313] The Rayleigh fading channel matrix from the kth terminal in the jth cell to the access network device in the ith cell is an M x M matrix, i.e. The channel estimation matrix from the kth terminal in the jth cell to the access network device in the ith cell is an M x M matrix, i.e. The channel error matrix from the kth terminal in the jth cell to the access network device in the ith cell is an M x M matrix, i.e. .

[0314] The channel noise (sum) superimposed in the signal received by the access network device in the ith cell from each terminal is denoted as , is modeled as a vector of additive white Gaussian noise superimposed in the channel, whose mean is and the covariance matrix is , denoted as the variance of the channel noise.

[0315] For example, each terminal in multiple cells transmits the uplink signal after encoding by the precoding matrix, and after wireless channel transmission, the uplink signal received by the access network device in the ith cell can be represented as formula (12).

[0316] Formula (12),

[0317] where i = 1, 2, …, Ku, and is regarded as the equivalent channel between the kth terminal in the jth cell and the access network device in the ith cell, then the uplink signal received by the access network device in the ith cell is further represented as formula (13).

[0318] Equation (13),

[0319] For example, the access network device of the ith cell actually receives the superposition of the uplink signals of all terminals in the ith cell, the uplink interference signals of all terminals in the jth cell, and channel noise, and the access network device of the ith cell needs to pass through a decoding matrix to obtain actual decoded received data .

[0320] The decoding matrix of the ith cell is , i = 1, 2, …, Ku. The uplink data sent by each terminal in the ith cell is recovered from the uplink signal received by the access network device of the ith cell. The decoding matrix of the ith cell is an Mxd matrix, that is, .

[0321] For example, the access network device of the ith cell receives the uplink signal, and after decoding by the decoding matrix, the actual uplink data received by the access network device of the ith cell is denoted as Equation (14).

[0322] Equation (14),

[0323] i = 1, 2, …, Ku. For example, in the uplink signal transmission process, the most ideal case is that the transmitted signal is the same as the received signal, that is, the target uplink data of the access network device of the ith cell is .

[0324] Through the above method, the actual uplink data received by the access network device of each cell in the AirComp system and the target uplink data can be obtained.

[0325] S1002, the access network device establishes an optimization problem to minimize the sum of the mean square errors of the actual uplink data and the target uplink data received by the access network device of each cell in the plurality of cells.

[0326] The optimization problem established by the access network device is used to design the precoding matrix and the decoding matrix.

[0327] Under the power constraint condition of the signals transmitted by each cell, according to the actual uplink data and the target uplink data received by the access network device of each cell in the plurality of cells, the access network device establishes an optimization problem for minimizing the sum of the mean square errors of the plurality of cells using the minimum mean square error (MMSE) criterion.

[0328] The access network device A of cell A is described.

[0329] For example, the minimum mean square error between the actual received uplink data and the target uplink data at the access network device A can be represented by equation (15).

[0330] Equation (15),

[0331]

[0332] wherein, represents a random vector , , , , , a random matrix , , , , , and the mathematical expectation of the additive white Gaussian noise vector superimposed in the channel. represents the square of the Frobenius norm of the matrix , and P represents the transmission power of any terminal in the cell A, the cell B and the cell C. It can be understood that the transmission power of any terminal in multiple cells can be different values, and the embodiments of the present application assume that the transmission power of any terminal in multiple cells is the same.

[0333] In equation (15), minimization can ensure that the access network device A correctly receives the uplink data transmitted by each terminal in the cell A, in equation (15), minimization can ensure that the access network device A receives the minimum uplink interference signal of each terminal in the cell B and the cell C, in equation (15), minimization can ensure that the error caused by the channel estimation error between each terminal in multiple cells and the access network device A is minimized, in equation (15), minimization can ensure that the influence of the channel noise superimposed on the channel between each terminal in multiple cells and the access network device A is minimized.

[0334] For example, the above is the mean square error at the access network device A of the cell A. Expanding the problem to the sum of the mean square errors between the actual received uplink data and the target uplink data at the access network device of each cell in the cell A, the cell B and the cell C is minimized, and the final optimization problem can be represented by equation (16).

[0335] Equation (16),

[0336] It can be understood that there are multiple cells in an actual AirComp system. Taking the number of cells as Ku and the number of terminals in each cell as Ka as an example, the access network device establishes an optimization problem that minimizes the sum of the mean square errors between the uplink data actually received by the access network device of each cell in multiple cells and the target uplink data.

[0337] The minimum mean square error between the uplink data actually received by the access network device of the i th cell and the target uplink data established by the access network device of the i th cell can be expressed as formula (17).

[0338] Formula (17),

[0339] Wherein, i = 1, 2, …, Ku, j = 1, 2, …, Ku. denotes the mathematical expectation of the random vector , the random matrix and the additive white Gaussian noise vector superimposed in the channel, denotes the square of the Frobenius norm of the matrix . It is assumed that the transmission power of each terminal is the same, and P represents the transmission power of any terminal in multiple cells. It can be understood that the transmission power of any terminal in multiple cells can be different values, and the embodiments of the present application assume that the transmission power of any terminal in multiple cells is the same. By taking the mathematical expectation of the random vector , the formula can be simplified to not containing .

[0340] The minimization of in formula (17) can ensure that the access network device of the i th cell correctly receives the uplink data sent by each terminal in the i th cell, the minimization of in formula (17) can ensure that the access network device of the i th cell receives the uplink interference signal of each terminal in other cells is minimized, the minimization of in formula (17) can ensure that the error caused by the channel estimation error of each terminal in multiple cells to the access network device of the i th cell is minimized, and the minimization of in formula (17) can ensure that the influence of the channel noise superimposed on the channel between each terminal in multiple cells and the access network device of the i th cell is minimized.

[0341] Exemplarily, the above is the mean square error at the access network device of the ith cell. Expanding the problem to the sum of the mean square error of the uplink data actually received by the access network device of each cell and the target uplink data in each cell, the final optimization problem can be expressed as formula (18).

[0342] Formula (18),

[0343] S1003, the access network device solves the optimization problem to obtain the solution of the precoding matrix, the formula of the decoding matrix and the Lagrange multiplier.

[0344] Exemplarily, the optimization problem of solving the sum of the mean square error of the uplink data actually received by the access network device of each cell and the target uplink data in cell A, cell B and cell C is described.

[0345] Exemplarily, the access network device can use the Lagrange method to solve the optimization problem shown in formula (18). Using the Lagrange method to solve the formula (18), the Lagrange function of the optimization problem can be expressed as formula (19).

[0346] Formula (19),

[0347] wherein, denotes the Lagrange multiplier, is used to convert the optimization problem containing the constraint condition into an unconstrained optimization problem.

[0348] According to wherein, denotes the square of the Frobenius norm of the matrix denotes the conjugate transpose of the matrix denotes the trace of the matrix in the parentheses, formula (20) can be further simplified. Formula (20),

[0349] When , it can be obtained that

[0350] wherein, denotes the expectation of the vector in the parentheses, denotes the column vector stacked by the matrix by column, denotes the conjugate transpose of denotes the variance of the matrix denotes the unit matrix. ​​​​denotes the matrix , denotes the conjugate transpose of the matrix , , is a matrix, denotes taking the trace of the matrix in the parentheses. The formula (21) can be further simplified as formula (22).

[0351] The formula (22),

[0352] By taking the mathematical expectation of the random matrix , the channel estimation error of each terminal in the jth cell to the access network device in the ith cell can be converted into the statistical characteristics of . Wherein, the channel error matrix corresponding to The covariance matrix of , denotes the variance of the channel error matrix between the kth terminal in the jth cell and the access network device in the ith cell The covariance matrix of the additive Gaussian white noise vector , denotes the variance of the additive Gaussian white noise vector superimposed in the signal received by the access network device in the ith cell.

[0353] Expanding the above formula, formula (22) is obtained:

[0354] The formula (22),

[0355] In formula (22), the unknown quantity is , and the rest can be calculated.

[0356] In formula (22), let , then formula (23) is obtained:

[0357] The formula (23),

[0358] It should be noted that L contains Ku summation terms after traversing i=1,2,……,Ku, denotes that the Ku summation terms in L are all differentiated with respect to , , , Therefore, L needs to be distinguished from i in the derivation of .

[0359] by right Taking differentiation as an example, when using and To differentiate, right Differentiation right Perform differentiation. When not using... To distinguish it from 'i' right Differentiation right Perform differentiation.

[0360] when hour and They are unrelated, because , ,as well as ,(in express conjugate, express (transpose of), and then formula (23) can be further simplified to formula (24).

[0361] Formula (24),

[0362] Further calculations can yield the decoding matrix. This is represented by formula (25).

[0363] Formula (25),

[0364] Among them, i=1,2,…,Ku.

[0365] Similarly, in formula (22), let Thus, we obtain formula (26).

[0366] Formula (26),

[0367] Similarly, in formula (23), L contains Ku summation terms after iterating through j=1,2,...,Ku. This means that each of the Ku summation terms in L represents a sum of terms on... , ... To perform differentiation, L needs to be used. With The differentiation of j in the derivative is necessary to achieve this.

[0368] by right For example, when using and are distinguished, the derivative of is the derivative of . Since and are independent of each other, it can be simplified as the derivative of , that is, so it can be known that here is actually the Lagrange multiplier of the relevant summation term, so it can be understood as is actually related to j, so can be written as .

[0369] Further, since , and , formula (26) can be further simplified as formula (27):

[0370] Formula (27),

[0371] is transformed to obtain formula (28):

[0372] Formula (28),

[0373] further calculation can obtain the first precoding matrix is expressed as formula (29).

[0374] Formula (29),

[0375] wherein, j=1, 2, …, Ku.

[0376] The above calculation process has determined the precoding matrix and the decoding matrix , and the value of is determined next, and the constraint condition of the optimization problem is known as . Therefore, . In formula (29), is denoted as , is denoted as , and formula (30) is obtained:

[0377] Formula (30),

[0378] Substitute formula (30) into formula (29) Formula (31) that satisfies formula (32) is:

[0379] Formula (31),

[0380] Alternatively, the solution of this equation can be obtained by using dichotomy or Newton iteration method wherein .

[0381] Finally, the first precoding matrix and the formula of the decoding matrix and the Lagrange multiplier are obtained through steps S1001-S1003.

[0382] By introducing the Lagrange multiplier, the originally constrained optimization problem can be converted into an unconstrained optimization problem, thereby simplifying the process of solving the optimization problem, so as to obtain a suitable precoding matrix and decoding matrix, which can minimize the sum of the mean square errors of the uplink data actually received by the access network device in each cell and the destination uplink data in each cell, and improve the accuracy of the access network device in receiving data. That is, while ensuring that the access network device in the cell correctly receives the signal sent by the terminal in the cell, the uplink data signal interference from other cells is minimized, and the influence of the channel estimation error and noise of each terminal to each access network device in each cell is minimized.

[0383] It should be understood that Figures 1 to 11 The flowchart or scenario diagram shown is only for understanding, and is not intended to limit the embodiments of the present application to the examples shown in the diagram. In fact, based on the examples in the specification, those skilled in the art can make equivalent transformations to obtain more implementation manners. Figures 1 to 11

[0384] The uplink data transmission method and the encoding and decoding matrix determination method provided by the embodiments of the present application are described in detail above in combination with Figures 1 to 11 The device embodiments of the present application will be described in detail below. It should be understood that the communication device of the embodiments of the present application can perform the method described in the foregoing embodiments of the present application, that is, the specific working processes of the following various products can refer to the corresponding processes in the foregoing method embodiments. Figures 12 to 13

[0385] ​​​​In the above embodiments, the terminal can perform some or all of the steps in the embodiments; the network device can perform some or all of the steps in the embodiments. These steps or operations are only examples, and the embodiments of the present application can also perform other operations or variations of various operations. In addition, various steps can be performed in different orders presented in various embodiments, and it is possible that not all operations in the embodiments of the present application are performed. Moreover, the magnitude of the serial number of each step does not mean the order of execution, the execution order of each process should be determined according to its function and inherent logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0386] Figure 12 is a schematic block diagram of a communication apparatus provided by the embodiments of the present application. The communication apparatus 1200 can perform the actions of the terminal, network device in the method shown in the above Figures 2 to 11 The above method embodiments involve all related contents of each step, which can be referred to the function description of the corresponding function module, and the technical effects can be referred to the above method embodiments, which will not be described here.

[0387] The communication apparatus 1200 can include a transceiver module 1201 and a processing module 1202. The communication apparatus 1200 can be a communication device, or a chip or other combination device or component with the above communication apparatus function applied to the communication device. When the communication apparatus 1200 is a communication device, the transceiver module 1201 can be a transceiver, which can include an antenna and a radio frequency circuit, etc. The processing module 1202 can be a processor (or processing circuit), for example, a baseband processor, which can include one or more central processing units (CPU). When the communication apparatus 1200 is a component with the above communication apparatus function, the transceiver module 1201 can be a radio frequency unit; the processing module 1202 can be a processor (or processing circuit), for example, a baseband processor. When the communication apparatus 1200 is a chip system, the transceiver module 1201 can be an input and output interface of a chip (for example, a baseband chip); the processing module 1202 can be a processor (or processing circuit) of the chip system, which can include one or more central processing units. It should be understood that the transceiver module 1201 in the embodiments of the present application can be realized by a transceiver or transceiver related circuit components; the processing module 1202 can be realized by a processor or processor related circuit components (or processing circuit).

[0388] For example, the transceiver module 1201 can be used to perform all transceiver operations performed by the communication apparatus in the embodiments shown in the above Figures 2 to 11 and / or other processes for supporting the technologies described herein; the processing module 1202 can be used to perform the steps of the above Figures 2 to 11All operations performed by the communication device in the embodiments shown, in addition to the transceiving operations, and / or other processes for supporting the techniques described herein.

[0389] As yet another implementation, Figure 12 The transceiver module 1201 in the communication device 1200 can be replaced by a transceiver that integrates the functions of the transceiver module 1201; the processing module 1202 can be replaced by a processor that integrates the functions of the processing module 1202. Further, Figure 12 The communication device 1200 shown can also include a memory.

[0390] The embodiments of the present application also provide a communication device 1300 as shown in Figure 13 The communication device 1300 can be a terminal or a chip or system on chip in the terminal; or a network device or a chip or system on chip in the network device. As shown in Figure 13 The communication device 1300 includes a first processor 1301, a transceiver 1302 and a communication line 1303.

[0391] Further, the communication device 1300 can also include a memory 1304. The first processor 1301, the memory 1304 and the transceiver 1302 can be connected through the communication line 1303.

[0392] The first processor 1301 is a central processing unit (CPU), a general processor, a network processor (NP), a digital signal processor (DSP), a microprocessor, a microcontroller, a programmable logic device (PLD) or any combination thereof. The first processor 1301 can also be other devices with processing functions, such as a circuit, a device or a software module, which are not limited.

[0393] The transceiver 1302 is configured to communicate with other devices or other communication networks. The other communication networks can be Ethernet, RAN, wireless local area networks (WLAN) and the like. The transceiver 1302 can be a module, a circuit, a transceiver or any device capable of communication.

[0394] The communication line 1303 is configured to transmit information between components included in the communication device 1300.

[0395] The memory 1304 is configured to store instructions. The instructions can be a computer program.

[0396] The memory 1304 may be a read-only memory (ROM) or other type of static storage device capable of storing static information and / or instructions; it may also be a random access memory (RAM) or other type of dynamic storage device capable of storing information and / or instructions; it may also be an electrically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM) or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital universal optical discs, Blu-ray discs, etc.), magnetic disk storage media or other magnetic storage devices, etc., without limitation.

[0397] It should be noted that the memory 1304 can exist independently of the first processor 1301 or can be integrated with the first processor 1301. The memory 1304 can be used to store instructions, program code, or some data, etc. The memory 1304 can be located inside or outside the communication device 1300, without limitation. The first processor 1301 is used to execute the instructions stored in the memory 1304 to implement the downlink resource configuration method provided in the following embodiments of this application.

[0398] In one example, the first processor 1301 may include one or more CPUs, for example... Figure 13 CPU0 and CPU1 in the CPU.

[0399] As an optional implementation, the communication device 1300 includes multiple processors, for example, besides Figure 13 In addition to the first processor 1301, it may also include a second processor 1307.

[0400] As an optional implementation, the communication device 1300 also includes an output device 1305 and an input device 1306. For example, the input device 1306 is a device such as a keyboard, mouse, microphone or joystick, and the output device 1305 is a device such as a display screen or speaker.

[0401] It should be noted that the communication device 1300 can be a desktop computer, laptop computer, network server, mobile phone, tablet computer, wireless terminal, embedded device, chip system, or other device. Figure 13 Equipment with a similar structure. Furthermore... Figure 13 The structural composition shown does not constitute a limitation on the communication device, except... Figure 13In addition to the components shown, the communication device can include more or fewer of the components shown, or combinations thereof, or different arrangements of the components.

[0402] In the embodiments of the present application, the chip system can be composed of a chip, or can include a chip and other discrete devices.

[0403] In addition, the actions, terms, etc. involved among the embodiments of the present application can be mutually referred to without limitation. The message name or parameter name in the message exchanged between the devices in the embodiments of the present application is only an example, and other names can also be used in the specific implementation without limitation.

[0404] The embodiments of the present application further provide a communication system, which includes the network device and the terminal as described above.

[0405] The embodiments of the present application further provide a computer program product, which can realize the functions of any of the method embodiments above when executed by a computer.

[0406] The embodiments of the present application further provide a computer program, which can realize the functions of any of the method embodiments above when executed by a computer.

[0407] The embodiments of the present application further provide a computer readable storage medium. All or part of the flow of the method embodiments above can be instructed by a computer program to relevant hardware to complete, and the program can be stored in the computer readable storage medium, and the program can include the flow of the method embodiments above when executed. The computer readable storage medium can be an internal storage unit of the terminal (including the data sending end and / or the data receiving end) of any of the embodiments above, for example, a hard disk or a memory of the terminal. The computer readable storage medium above can also be an external storage device of the terminal, for example, a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. Further, the computer readable storage medium above can include both the internal storage unit and the external storage device of the terminal. The computer readable storage medium above is used to store the computer program above and other programs and data required by the terminal. The computer readable storage medium above can also be used to temporarily store the data that has been output or will be output.

[0408] In several embodiments provided in the present application, it should be understood that the disclosed apparatus and method can be implemented by other manners. For example, the apparatus embodiments described above are merely illustrative, for example, the division of the modules or units is merely a logical function division, and actual implementation can have another division manner, for example, a plurality of units or components can be combined or integrated into another apparatus, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the units or components shown or discussed can be indirect coupling or communication connection through some interfaces, apparatuses or units, and can be electrical, mechanical or other forms.

[0409] The units described as separate components can or can not be physically separate, and the components shown as units can be one physical unit or a plurality of physical units, that is, can be located in one place, or can be distributed to a plurality of different places. Part or all of the units can be selected according to actual needs to achieve the purpose of the embodiment scheme.

[0410] In addition, the functional units in each embodiment of the present application can be integrated in one processing unit, or each unit can be physically present separately, or two or more units can be integrated in one unit. The integrated unit can be realized in the form of hardware or in the form of a software functional unit.

[0411] When the integrated unit is realized in the form of a software functional unit and sold or used as an independent product, it can be stored in a readable storage medium. Based on this understanding, the technical solutions of the embodiments of the present application can be embodied in the form of a software product in essence or all or part of the technical solutions. The software product is stored in a storage medium, and includes a plurality of instructions for causing an apparatus (which can be a single-chip microcomputer, a chip, etc.) or a processor to execute all or part of the steps of the method described in each embodiment of the present application. The foregoing storage medium includes: a U disk, a mobile hard disk, a ROM, a RAM, a magnetic disk or an optical disk, and various storage program codes.

[0412] The above embodiments are only used to illustrate the technical solutions of the present application, and not to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that they can modify the technical solutions recorded in the foregoing embodiments, or make equivalent replacement for part of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for data transmission based on over-the-air computation of channel estimates, the method comprising: The method is applied to a first access network device corresponding to a first cell, and comprises the following steps: Receiving an uplink signal from a terminal in the first cell; Decoding the uplink signal by using a decoding matrix of the first access network device to obtain uplink data; wherein the decoding matrix of the first access network device is calculated based on a first precoding matrix of multiple cells, a second precoding matrix of each terminal in the multiple cells, an equivalent channel matrix between each terminal in the multiple cells and the first access network device, a variance of channel noise superimposed in a channel between each terminal in the multiple cells and the first access network device, and a variance of channel estimation error between each terminal in the multiple cells and the first access network device; the equivalent channel matrix is a product of an estimated channel matrix between each terminal in the multiple cells and the first access network device and the corresponding second precoding matrix; the multiple cells include the first cell; The first precoding matrix of the first cell is used to align uplink interference data received by the first access network device from other cells in the multiple cells except the first cell, and the second precoding matrix of a first terminal in the first cell is used to align uplink data sent by each terminal in the first cell to the first access network device.

2. The method of claim 1, wherein, The first precoding matrix of the first cell is different from the first precoding matrix of the other cells; The second precoding matrix of the first terminal is different from the second precoding matrix of other terminals in the first cell, and is different from the second precoding matrix of terminals in the other cells.

3. The method according to claim 1 or 2, characterized in that, Each of the first access network device and the first terminal is configured with M antennas, the uplink data is multi-stream data, and the multi-stream data includes d data streams; The precoding matrix is an Mxd matrix, the first precoding matrix of the first cell is an Mxd matrix, and the second precoding matrix of the first terminal is an MxM matrix.

4. The method of claim 3, wherein, Before the step of decoding the uplink signal by using the decoding matrix of the first access network device to obtain uplink data, the method further comprises the following steps: Receiving an nth round precoding matrix from terminals in the multiple cells; the nth round precoding matrix of the first terminal includes an nth round first precoding matrix of the first cell and a second precoding matrix of the first terminal, n is sequentially taken from a set {1, 2, 3, …, N-1}, the first round first precoding matrix of the first cell is a matrix satisfying a quasi-unitary constraint, the conjugate transpose of the matrix satisfying the quasi-unitary constraint multiplied by the matrix satisfying the quasi-unitary constraint is equal to a unit matrix, and the matrix satisfying the quasi-unitary constraint is an Mxd matrix; the second precoding matrix of the first terminal is an inverse matrix of a channel estimation matrix between the first terminal and the first access network device. calculating an n-th round decoding matrix of the first cell based on an n-th round first precoding matrix of the plurality of cells, a second precoding matrix of each terminal in the plurality of cells, an equivalent channel matrix between each terminal in the plurality of cells and the first access network device, a variance of channel noise superimposed in a channel between each terminal in the plurality of cells and the first access network device, and a variance of channel estimation error between each terminal in the plurality of cells and the first access network device; the equivalent channel matrix is a product of a channel estimation matrix between each terminal in the plurality of cells and the first access network device and the corresponding second precoding matrix; the plurality of cells include the first cell and other cells.

5. The method of claim 4, wherein, After the calculating the n-th round decoding matrix of the first cell, the method further includes: sending the n-th round decoding matrix of the first cell to the first terminal, the n-th round decoding matrix of the first cell being used by the first terminal to calculate an n+1-th round first precoding matrix of the first cell; wherein the n+1-th round precoding matrix of the first terminal includes the n+1-th round first precoding matrix of the first cell and the second precoding matrix of the first terminal.

6. The method of claim 4, wherein, After the calculating the n-th round decoding matrix of the first cell, the method further includes: receiving an N-th round precoding matrix from terminals of the plurality of cells; the N-th round precoding matrix of the first terminal includes an N-th round first precoding matrix of the first cell and a second precoding matrix of the first terminal; calculating an N-th round decoding matrix of the first cell based on an N-th round first precoding matrix of the plurality of cells, a second precoding matrix of each terminal in the plurality of cells, an equivalent channel matrix between each terminal in the plurality of cells and the first access network device, a variance of channel noise superimposed in a channel between each terminal in the plurality of cells and the first access network device, and a variance of channel estimation error between each terminal in the plurality of cells and the first access network device.

7. The method of claim 5, wherein, The calculating the n-th round decoding matrix of the first cell based on the n-th round first precoding matrix of the plurality of cells, the second precoding matrix of each terminal in the plurality of cells, the equivalent channel matrix between each terminal in the plurality of cells and the first access network device, the variance of channel noise superimposed in the channel between each terminal in the plurality of cells and the first access network device, and the variance of channel estimation error between each terminal in the plurality of cells and the first access network device includes: ； wherein, denotes the equivalent channel matrix between the kth terminal in the jth cell and the access network device in the ith cell, denotes the nth round of first precoding matrix of the jth cell, denotes the conjugate transpose of the nth round of first precoding matrix of the jth cell, denotes the conjugate transpose of the equivalent channel matrix between the kth terminal in the jth cell and the access network device in the ith cell, denotes the variance of the channel estimation error between the kth terminal in the jth cell and the access network device in the ith cell, denotes the trace of the matrix in the parentheses, denotes the second precoding matrix of the kth terminal in the jth cell, denotes the conjugate matrix of the second precoding matrix of the kth terminal in the jth cell, denotes the variance of the additive white Gaussian noise vector superimposed in the channel, denotes the identity matrix, denotes the equivalent channel matrix between the kth terminal in the ith cell and the access network device in the ith cell, denotes the nth round of first precoding matrix of the ith cell, i, j = 1, …, Ku, k = 1, …, Ka, there are Ku cells in total, and each cell has Ka terminals.

8. The method of claim 7, wherein, The first cell's first round first precoding matrix is a randomly generated Mxd matrix satisfying quasi-unitary constraint.

9. A method for data transmission based on over-the-air computation of channel estimates, the method comprising: The method is applied to a first terminal, the first terminal being a terminal of a first cell, and the method includes: The method is applied to a first terminal, the first terminal being a terminal of a first cell, and the method includes: obtaining a precoding matrix of the first terminal; wherein the precoding matrix of the first terminal comprises a first precoding matrix of the first cell and a second precoding matrix of the first terminal, the first precoding matrix of the first cell being used to align uplink interference data received by the first access network device from other cells in the plurality of cells except the first cell, the first access network device being an access network device of the first cell, and the second precoding matrix of the first terminal being used to align uplink data sent by each terminal in the first cell to the first access network device; sending an uplink signal to the first access network device; wherein the uplink signal is encoded by the precoding matrix of the first terminal.

10. The method of claim 9, wherein, The first precoding matrix of the first cell is calculated based on a decoding matrix of the plurality of cells, a second precoding matrix of each terminal in the first cell, an equivalent channel matrix between each terminal in the first cell and access network devices of the plurality of cells, and a variance of channel estimation error between each terminal in the plurality of cells and the first access network device, and a plurality of Lagrange multipliers.

11. The method of claim 10, wherein, The first precoding matrix of the first cell is different from the first precoding matrix of the other cells. The second precoding matrix of the first terminal is different from the second precoding matrix of other terminals in the first cell, and the second precoding matrix of the first terminal is different from the second precoding matrix of terminals in the other cells.

12. The method according to any one of claims 9-11, characterized in that, The first access network device and the first terminal are respectively configured with M antennas, the uplink data is multi-stream data, and the multi-stream data comprises d data streams. The precoding matrix is an Mxd matrix, the first precoding matrix of the first cell is an Mxd matrix, and the second precoding matrix of the first terminal is an MxM matrix.

13. The method of claim 12, wherein, The obtaining of the precoding matrix of the first terminal comprises: obtaining an nth round precoding matrix of the first terminal, the nth round precoding matrix of the first terminal comprising an nth round first precoding matrix of the first cell and a second precoding matrix of the first terminal, n being sequentially taken from the set {1, 2, 3, …, N-1}, the first round first precoding matrix of the first cell being a matrix satisfying a quasi-unitary constraint, the conjugate transpose of the matrix satisfying the quasi-unitary constraint multiplied by the matrix satisfying the quasi-unitary constraint being equal to an identity matrix, and the matrix satisfying the quasi-unitary constraint being an Mxd matrix; and the second precoding matrix of the first terminal being an inverse matrix of a channel estimation matrix between the first terminal and the first access network device; sending the nth round precoding matrix of the first terminal to the first access network device. receive an n-th round decoding matrix of the first cell from the first access network device, the n-th round decoding matrix of the first cell being calculated based on an n-th round first precoding matrix of the plurality of cells, a second precoding matrix of each terminal in the plurality of cells, an equivalent channel matrix between each terminal in the plurality of cells and the first access network device, a variance of channel noise superimposed in a channel between each terminal in the plurality of cells and the first access network device, and a variance of channel estimation error between each terminal in the plurality of cells and the first access network device; the equivalent channel matrix being a product of a channel estimation matrix between each terminal in the plurality of cells and the first access network device and the corresponding second precoding matrix; calculate an n+1-th round first precoding matrix of the first cell based on the n-th round decoding matrix of the plurality of cells, the second precoding matrix of each terminal in the first cell, the equivalent channel matrix between each terminal in the first cell and access network devices of the plurality of cells, the variance of channel estimation error between each terminal in the plurality of cells and the first access network device, and a plurality of Lagrange multipliers; wherein the n+1-th round precoding matrix of the first terminal comprises the n+1-th round first precoding matrix of the first cell and the second precoding matrix of the first terminal.

14. The method of claim 13, wherein, The method further comprises: obtaining the plurality of Lagrange multipliers; wherein the plurality of Lagrange multipliers correspond one-to-one to the plurality of cells, the plurality of cells comprising the first cell and the other cells; the Lagrange multiplier being a Lagrange coefficient in a Lagrange function of an optimization problem established by designing a suitable precoding matrix and a decoding matrix; The suitable precoding matrix and the decoding matrix can minimize the sum of mean square errors between actual received uplink data and target uplink data of the access network device of each cell in the plurality of cells.

15. The method according to claim 13 or 14, characterized in that, The calculation of the n+1-th round first precoding matrix of the first cell based on the n-th round decoding matrix of the plurality of cells, the second precoding matrix of each terminal in the first cell, the equivalent channel matrix between each terminal in the first cell and access network devices of the plurality of cells, the variance of channel estimation error between each terminal in the plurality of cells and the first access network device, and a plurality of Lagrange multipliers comprises: ； wherein, Hjk,i represents an equivalent channel matrix between the kth terminal in the jth cell and the access network device in the ith cell, , Hjk,i represents a channel estimation matrix between the kth terminal in the jth cell and the access network device in the ith cell, Wjk represents a second precoding matrix of the kth terminal in the jth cell, Hjk,i represents a conjugate transpose of the equivalent channel matrix between the kth terminal in the jth cell and the access network device in the ith cell, Wjk represents a decoding matrix of the ith cell in the nth round, Wjk represents a conjugate transpose of the decoding matrix of the ith cell in the nth round, σ2jk,i represents a variance of a channel estimation error between the kth terminal in the jth cell and the access network device in the ith cell, tr() represents a trace of a matrix in parentheses, Wjk represents a conjugate matrix of the second precoding matrix of the kth terminal in the jth cell, λj represents a Lagrange multiplier of the jth cell, I represents a unit matrix, Hjk,j represents a conjugate transpose of the equivalent channel matrix between the kth terminal in the jth cell and the access network device in the jth cell, Wjk represents a decoding matrix of the jth cell in the nth round, i, j = 1, …, Ku, k = 1, …, Ka, there are Ku cells in total, and each cell has Ka terminals.

16. The method of claim 14, wherein, The first precoding matrix of the first cell in the first round is a randomly generated Mxd matrix satisfying quasi-unitary constraints.

17. A method for data transmission based on over-the-air computation of channel estimates, the method comprising: The method is applied to a first access network device corresponding to a first cell, and the method comprises: receive the nth round precoding matrix of the terminal from a plurality of cells; the plurality of cells include the first cell, the first terminal of the first cell includes the nth round first precoding matrix of the first cell and the second precoding matrix of the first terminal, n is sequentially taken in {1, 2, 3 …… N-1}, the first round first precoding matrix of the first cell is a matrix satisfying quasi-unitary constraint, the conjugate transpose of the matrix satisfying quasi-unitary constraint multiplied by the matrix satisfying quasi-unitary constraint is equal to the unit matrix, the matrix satisfying quasi-unitary constraint is Mxd matrix, M roots of antennas are respectively configured in the first access network device and the first terminal, the uplink data sent by the first terminal to the first access network device is multi-flow data, the multi-flow data includes d data flows; the second precoding matrix of the first terminal is the inverse matrix of the channel estimation matrix between the first terminal and the first access network device; based on the nth round first precoding matrix of the plurality of cells, the second precoding matrix of each terminal in the plurality of cells, the equivalent channel matrix between each terminal in the plurality of cells and the first access network device, the variance of the channel noise superimposed in the channel between each terminal in the plurality of cells and the first access network device and the variance of the channel estimation error between each terminal in the plurality of cells and the first access network device, calculate the nth round decoding matrix of the first cell; the equivalent channel matrix is the product of the channel estimation matrix between each terminal in the plurality of cells and the first access network device and the corresponding second precoding matrix; the plurality of cells include the first cell and other cells; send the nth round decoding matrix of the first cell to the first terminal, the nth round decoding matrix of the first cell is used for the first terminal to calculate the nth+1 round first precoding matrix of the first cell; wherein the nth+1 round precoding matrix of the first terminal includes the nth+1 round first precoding matrix of the first cell and the second precoding matrix of the first terminal.

18. The method of claim 17, wherein, after the calculation of the nth round decoding matrix of the first cell, the method further comprises: receive the Nth round precoding matrix of the terminal from the plurality of cells; the Nth round precoding matrix of the first terminal includes the Nth round first precoding matrix of the first cell and the second precoding matrix of the first terminal; based on the Nth round first precoding matrix of the plurality of cells, the second precoding matrix of each terminal in the plurality of cells, the equivalent channel matrix between each terminal in the plurality of cells and the first access network device, the variance of the channel noise superimposed in the channel between each terminal in the plurality of cells and the first access network device and the variance of the channel estimation error between each terminal in the plurality of cells and the first access network device, calculate the Nth round decoding matrix of the first cell.

19. The method of claim 17, wherein, The first precoding matrix of the first cell is used to align uplink interference data received by the first access network device from the other cells, and the second precoding matrix of the first terminal is used to align uplink data sent by each terminal in the first cell to the first access network device.

20. The method of any one of claims 17-19, wherein, The first precoding matrix of the first cell is different from the first precoding matrix of the other cells. The second precoding matrix of the first terminal is different from the second precoding matrix of other terminals in the first cell, and the second precoding matrix of the first terminal is different from the second precoding matrix of terminals in the other cells.

21. The method of any one of claims 17-19, wherein The precoding matrix is an Mxd matrix, the first precoding matrix of the first cell is an Mxd matrix, and the second precoding matrix of the first terminal is an MxM matrix.

22. The method of any one of claims 17-19, wherein, The n-th round decoding matrix of the first cell is calculated based on the n-th round first precoding matrix of the plurality of cells, the second precoding matrix of each terminal in the plurality of cells, the equivalent channel matrix between each terminal in the plurality of cells and the first access network device, the variance of the channel noise superimposed in the channel between each terminal in the plurality of cells and the first access network device, and the variance of the channel estimation error between each terminal in the plurality of cells and the first access network device, and the n-th round decoding matrix of the first cell is calculated based on the n-th round first precoding matrix of the plurality of cells, the second precoding matrix of each terminal in the plurality of cells, the equivalent channel matrix between each terminal in the plurality of cells and the first access network device, the variance of the channel noise superimposed in the channel between each terminal in the plurality of cells and the first access network device, and the variance of the channel estimation error between each terminal in the plurality of cells and the first access network device. ； wherein, denotes the equivalent channel matrix between the kth terminal in the jth cell and the access network device in the ith cell, denotes the nth round of first precoding matrix of the jth cell, denotes the conjugate transpose of the nth round of first precoding matrix of the jth cell, denotes the conjugate transpose of the equivalent channel matrix between the kth terminal in the jth cell and the access network device in the ith cell, denotes the variance of the channel estimation error between the kth terminal in the jth cell and the access network device in the ith cell, denotes the trace of the matrix in the parentheses, denotes the second precoding matrix of the kth terminal in the jth cell, denotes the conjugate matrix of the second precoding matrix of the kth terminal in the jth cell, denotes the variance of the additive white Gaussian noise vector superimposed in the channel, denotes the identity matrix, denotes the equivalent channel matrix between the kth terminal in the ith cell and the access network device in the ith cell, denotes the nth round of first precoding matrix of the ith cell, i, j = 1, …, Ku, k = 1, …, Ka, there are Ku cells in total, and each cell has Ka terminals.

23. A method for data transmission based on over-the-air computation of channel estimates, the method comprising: The method is applied to a first terminal, which is a terminal of a first cell, and the method comprises: The n-th round precoding matrix of the first terminal is obtained, the n-th round precoding matrix of the first terminal comprises the n-th round first precoding matrix of the first cell and the second precoding matrix of the first terminal, n is sequentially taken from the set {1, 2, 3, …, N-1}, the first round first precoding matrix of the first cell is a matrix satisfying a quasi-unitary constraint, the conjugate transpose of the matrix satisfying the quasi-unitary constraint multiplied by the matrix satisfying the quasi-unitary constraint equals a unit matrix, the matrix satisfying the quasi-unitary constraint is an Mxd matrix, M antennas are respectively configured in the first access network device and the first terminal, the uplink data sent by the first terminal to the first access network device is multi-stream data, the multi-stream data comprises d data streams, the second precoding matrix of the first terminal is an inverse matrix of a channel estimation matrix between the first terminal and the first access network device, and the first access network device is an access network device of the first cell. The n-th round precoding matrix of the first terminal is sent to the first access network device. receive an nth round decoding matrix of the first cell from the first access network device, the nth round decoding matrix of the first cell being calculated based on an nth round first precoding matrix of a plurality of cells, a second precoding matrix of each terminal in the plurality of cells, an equivalent channel matrix between each terminal in the plurality of cells and the first access network device, a variance of channel noise superimposed in a channel between each terminal in the plurality of cells and the first access network device, and a variance of channel estimation error between each terminal in the plurality of cells and the first access network device; the equivalent channel matrix being a product of a channel estimation matrix between each terminal in the plurality of cells and the first access network device and the corresponding second precoding matrix; the plurality of cells including the first cell and other cells; calculate an (n+1)th round first precoding matrix of the first cell based on the nth round decoding matrix of the plurality of cells, the second precoding matrix of each terminal in the first cell, the equivalent channel matrix between each terminal in the first cell and access network devices of the plurality of cells, the variance of channel estimation error between each terminal in the plurality of cells and the first access network device, and a plurality of Lagrange multipliers; wherein the (n+1)th round precoding matrix of the first terminal includes the (n+1)th round first precoding matrix of the first cell and the second precoding matrix of the first terminal.

24. The method of claim 23, wherein, The first precoding matrix of the first cell is used to align uplink interference data received by the first access network device from the other cells, and the second precoding matrix of the first terminal is used to align uplink data sent by each terminal in the first cell to the first access network device.

25. The method of claim 23 or 24, wherein, The first precoding matrix of the first cell is different from the first precoding matrix of the other cells. The second precoding matrix of the first terminal is different from the second precoding matrix of other terminals in the first cell, and the second precoding matrix of the first terminal is different from the second precoding matrix of terminals in the other cells.

26. The method of claim 23 or 24, wherein The precoding matrix is an Mxd matrix, the first precoding matrix of the first cell is an Mxd matrix, and the second precoding matrix of the first terminal is an MxM matrix.

27. The method of claim 23 or 24, wherein, The method further comprises: obtaining the plurality of Lagrange multipliers; wherein the plurality of Lagrange multipliers correspond one-to-one to the plurality of cells; and the Lagrange multiplier is a Lagrange coefficient in a Lagrange function of an optimization problem established by designing a suitable precoding matrix and a decoding matrix. The suitable precoding matrix and the decoding matrix can minimize the sum of mean square errors of uplink data actually received by an access network device of each cell in the plurality of cells and target uplink data.

28. The method of claim 23 or 24, wherein, The first precoding matrix of the first cell in the n+1th round is calculated based on the nth round decoding matrix of the plurality of cells, the second precoding matrix of each terminal in the first cell, the equivalent channel matrix between each terminal in the first cell and the access network device of the plurality of cells, the variance of the channel estimation error between each terminal in the plurality of cells and the first access network device, and a plurality of Lagrange multipliers, and comprises the following steps: ； wherein, Hjk,i represents an equivalent channel matrix between the kth terminal in the jth cell and the access network device in the ith cell, , Hjk,i represents a channel estimation matrix between the kth terminal in the jth cell and the access network device in the ith cell, Wjk represents a second precoding matrix of the kth terminal in the jth cell, Hjk,i represents a conjugate transpose of the equivalent channel matrix between the kth terminal in the jth cell and the access network device in the ith cell, Wjk represents a decoding matrix of the ith cell in the nth round, Wjk represents a conjugate transpose of the decoding matrix of the ith cell in the nth round, σjk,i represents a variance of a channel estimation error between the kth terminal in the jth cell and the access network device in the ith cell, tr() represents a trace of a matrix in parentheses, Wjk represents a conjugate matrix of the second precoding matrix of the kth terminal in the jth cell, λjk represents a Lagrange multiplier of the jth cell, I represents a unit matrix, Hjk,i represents a conjugate transpose of the equivalent channel matrix between the kth terminal in the jth cell and the access network device in the jth cell, Wjk represents a decoding matrix of the jth cell in the nth round, i, j = 1, …, Ku, k = 1, …, Ka, there are Ku cells in total, and each cell has Ka terminals.

29. A communications device, characterized by The communication device comprises a processor; the processor is used to run a computer program or instruction, so that the method as claimed in any one of claims 1-8 is executed, or so that the method as claimed in any one of claims 17-22 is executed, or so that the method as claimed in any one of claims 9-16 is executed, or so that the method as claimed in any one of claims 23-28 is executed.

30. A communications device, characterized by The communication device comprises an interface circuit and a logic circuit; the interface circuit is used to input and / or output information; the logic circuit is used to execute the method as claimed in any one of claims 1-8, or execute the method as claimed in any one of claims 17-22, or execute the method as claimed in any one of claims 9-16, or execute the method as claimed in any one of claims 23-28.

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