CN-117544202-B - MIMO transmission method and system using fluid antenna

CN117544202BCN 117544202 BCN117544202 BCN 117544202BCN-117544202-B

Abstract

The invention discloses a MIMO transmission method and a system using fluid antennas, wherein a plurality of fluid antennas which can freely move in a given area are respectively deployed at a transmitter side and a receiver side. According to the method, the optimization problem for maximizing the system reachable rate is established by establishing a corresponding channel model and according to statistical channel information, the transmitting fluid antenna position, the receiving fluid antenna position and the transmitting covariance matrix are taken as optimization variables, and the optimization problem is solved by means of alternate optimization, cauchy-Schwarz inequality and Taylor expansion, so that the reachable rate is maximized. Compared with the situation that the traditional MIMO uses the fixed-position antenna, the invention can utilize more space degrees of freedom to obtain higher reachable rate and diversity gain.

Inventors

YOU LI
YE YUQI
GUO XINYI
HUANG KELIN
Che Haohong
GAO XIQI

Assignees

东南大学

Dates

Publication Date: 20260508
Application Date: 20231110

Claims (9)

1. MIMO transmission method using fluid antennas, characterized in that the transmitter and receiver sides are each provided with a plurality of fluid antennas capable of freely moving in a given area, by establishing a channel model and constructing an optimization problem for maximizing the achievable rate of the system based on statistical channel information, by optimizing the transmitting fluid antenna positions Fluid receiving antenna position Transmission covariance matrix Optimizing the system achievable rate, wherein the optimization problem is expressed as: ; Wherein N and M are the number of the transmitting fluid antenna and the receiving fluid antenna respectively, And Channel matrix for a region where a transmitting fluid antenna and a receiving fluid antenna are movable, respectively , Is an emission area Origin to receiving area of (c) Is provided with a path response matrix of origin, And The number of transmit paths and receive paths respectively, Is that A response matrix of the individual transmitting fluid antennas, Is that The individual receiving fluid antennas respond to the matrix, Is that The dimensional identity matrix is used to determine the identity of the object, For the minimum distance required between the fluid antennas, At the time of the maximum transmission power, Representing the determinant of the matrix, The two norms of the vector quantity are indicated, The representation is a trace of the matrix, Representation of variables The desire is to be found that, Representing the variance of the complex additive Gaussian white noise, solving the optimization problem using alternating optimization, cauchy-Schwarz inequality and Taylor expansion, including replacing the original objective function with its immediate upper bound using the Jensen inequality Decomposing the original problem into a transmission covariance matrix by using alternate optimization Optimization problem, receiving fluid antenna position Optimization problem and transmit fluid antenna position Optimizing problem, setting iteration frequency indication Solving the transmit covariance matrix using the Cauchy-Schwarz inequality Optimizing problem, solving the receiving fluid antenna position by utilizing antenna position variable decoupling and Taylor expansion Solving the transmitting fluid antenna position by using Cauchy-Schwarz inequality, antenna position variable decoupling and Taylor expansion Optimization problem, will be the first Rate value obtained by multiple iterations and the first Comparing the results of the iterations if the difference between the results is less than a set threshold Terminating the iteration, otherwise, repeating the iteration times Adding 1, and continuing to carry out iterative solution.
2. The MIMO transmission method utilizing the fluid antenna according to claim 1, wherein the statistical channel state information is obtained by means of user feedback, direct estimation by the base station, or by means of an uplink sounding signal.
3. The MIMO transmission method utilizing a fluid antenna according to claim 1, wherein the channel model, for the transmitter section, is written as the th The elevation angle and the azimuth angle of each transmitting path are respectively And In the first place In the transmission path, the first Positions of the transmitting fluid antennas With the origin point The propagation distance difference between them is First, a third step The first transmission path The signal phase difference between the transmitting fluid antenna and the origin is Wherein The emission response vector is: ; All of The response matrix of the individual transmitting fluid antennas is: 。
4. The MIMO transmission method utilizing a fluid antenna as recited in claim 1, wherein said channel model, for the receiver section, states a first The elevation angle and the azimuth angle of each receiving path are respectively And In the first place In the receiving path, the first The position of the fluid-receiving antennas With the origin point The propagation distance difference between them is First, a third step The first transmission path The signal phase difference between the fluid receiving antenna and the origin is Wherein The received response vector is: ; All of The response matrix of the individual receiving fluid antennas is: 。
5. The MIMO transmission method utilizing a fluid antenna according to claim 1, wherein the raw objective function is a close-up boundary The method comprises the following steps: , wherein, Is the first The transmission path and the first Response coefficients between the receive paths Is a variance of (c).
6. The MIMO transmission method utilizing the fluid antenna as recited in claim 1, wherein the transmit covariance matrix is solved The optimization problem specifically comprises: transmit covariance matrix The optimization problem is expressed as: ; the objective function is rewritten as follows from the Cauchy-Schwarz inequality: ; wherein the condition for the equation to be satisfied is Is that Is based on the target function when the maximum value is reached Is that Multiple of (2) and These two conditions are calculated Is a solution to the optimization of (3).
7. The MIMO transmission method utilizing a fluid antenna according to claim 1, wherein the received fluid antenna position is solved The optimization problem specifically comprises: Receiving fluid antenna location The optimization problem is expressed as: ; Wherein, the Is the first The transmission path and the first Response coefficients between the receive paths Using antenna position variable decoupling to convert the optimization problem into the following problem, and solving the problem through second-order Taylor expansion: ; Wherein, the Is a matrix Middle (f) The column vector is used to determine the position of the column, , Is a matrix Is removed from Remaining behind The dimension matrix is used to determine the dimensions of the matrix, , Is that And (5) a dimensional identity matrix.
8. The MIMO transmission method utilizing a fluid antenna as recited in claim 1, wherein the transmit fluid antenna position is solved The optimization problem specifically comprises: Transmitting fluid antenna location The optimization problem is expressed as: ; And (3) decoupling by using a Cauchy-Schwarz inequality and an antenna position variable, converting the optimization problem into the following problem, and solving the following problem through second-order Taylor expansion: ; Wherein, the Is a matrix Middle (f) The column vector is used to determine the position of the column, 。
9. MIMO transmission system using fluid antennas, characterized by comprising a transmitter, a receiver and a rate optimization module, both the transmitter and the receiver side deploying a plurality of fluid antennas capable of free movement in a given area, the rate optimization module creating a channel model and constructing optimization problems maximizing the achievable rate of the system based on statistical channel information by optimizing the transmit fluid antenna position Fluid receiving antenna position Transmission covariance matrix Optimizing the system achievable rate, wherein the optimization problem is expressed as: ; Wherein N and M are the number of the transmitting fluid antenna and the receiving fluid antenna respectively, And Channel matrix for a region where a transmitting fluid antenna and a receiving fluid antenna are movable, respectively , Is an emission area Origin to receiving area of (c) Is provided with a path response matrix of origin, And The number of transmit paths and receive paths respectively, Is that A response matrix of the individual transmitting fluid antennas, Is that The individual receiving fluid antennas respond to the matrix, Is that The dimensional identity matrix is used to determine the identity of the object, For the minimum distance required between the fluid antennas, At the time of the maximum transmission power, Representing the determinant of the matrix, The two norms of the vector quantity are indicated, The representation is a trace of the matrix, Representation of variables The desire is to be found that, Representing the variance of the complex additive Gaussian white noise, solving the optimization problem using alternating optimization, cauchy-Schwarz inequality and Taylor expansion, including replacing the original objective function with its immediate upper bound using the Jensen inequality Decomposing the original problem into a transmission covariance matrix by using alternate optimization Optimization problem, receiving fluid antenna position Optimization problem and transmit fluid antenna position Optimizing problem, setting iteration frequency indication Solving the transmit covariance matrix using the Cauchy-Schwarz inequality Optimizing problem, solving the receiving fluid antenna position by utilizing antenna position variable decoupling and Taylor expansion Solving the transmitting fluid antenna position by using Cauchy-Schwarz inequality, antenna position variable decoupling and Taylor expansion Optimization problem, will be the first Rate value obtained by multiple iterations and the first Comparing the results of the iterations if the difference between the results is less than a set threshold Terminating the iteration, otherwise, repeating the iteration times Adding 1, and continuing to carry out iterative solution.

Description

MIMO transmission method and system using fluid antenna Technical Field The present invention relates to the field of wireless communication and fluid antennas, and in particular, to a MIMO transmission method and system using fluid antennas. Background The evolution from single antenna or single input single output to multiple antenna or multiple input multiple output has been an important trend in the evolution of wireless communication systems over the past decades. MIMO technology significantly improves the capacity and reliability of wireless communications by utilizing spatial multiplexing, interference suppression, beamforming, and diversity gain. However, existing communication systems do not take full advantage of the spatial freedom in the area where a given transmitter and receiver are located due to the antenna being deployed in a fixed location. To overcome this limitation, fluid antenna technology has recently been introduced so that the transmitter or receiver side antenna can be freely moved within a designated area. By utilizing more degrees of freedom in the spatial domain, fluid antennas and MIMO can be combined to achieve higher spatial diversity gains. Existing fluid antenna papers all utilize instantaneous channel state information. However, it is often difficult to obtain instantaneous channel state information in systems that utilize fluid antennas because of channel variations caused by variations in antenna position. On the other hand, the slowly varying nature of the statistical channel state information makes it relatively easy to obtain. For this, it is necessary to study a MIMO transmission scheme using fluid antennas and using statistical channel state information therein. Disclosure of Invention Aiming at the defects of the prior art, the invention aims to provide a MIMO transmission method and a system using fluid antennas, which can optimize the achievable rate of the system and reduce the complexity of realizing the optimization process aiming at the scene that a plurality of fluid antennas are deployed at both the transmitter side and the receiver side, so that the implementation is convenient. The technical scheme is that in order to achieve the aim of the invention, the invention adopts the following technical scheme: MIMO transmission method using fluid antennas, where the transmitter and receiver sides each deploy multiple fluid antennas that can move freely within a given area, by building a channel model and constructing an optimization problem that maximizes the system achievable rate based on statistical channel information, by optimizing the transmit fluid antenna positions Receiving fluid antenna locationAnd a transmit covariance matrix Q-optimizing the system achievable rate, the optimization problem expressed as: ||tk-tl||2≥D,k,l=1,2,...,N,k≠l, ||rk-rl||2≥D,k,l=1,2,...,M,k≠l, tr(Q)≤Pmax Wherein N and M are the number of the transmitting fluid antenna and the receiving fluid antenna respectively, AndThe channel matrix H (t, r) =f H (r) Σg (t) for the region where the transmit fluid antenna and the receive fluid antenna are movable, respectively,For the path response matrix from the origin of the transmit region t 0＝(0,0)T to the origin of the receive region r 0＝(0,0)T, L t and L r are the number of transmit and receive paths respectively,For a response matrix of N transmitting fluid antennas,For M receiving fluid antenna response matrices, I M is an M x M dimension identity matrix, D is the minimum distance required between the fluid antennas, P max is the maximum transmit power, det (·) represents the determinant of the matrix, 2 represents the vector quantity two norms, tr (·) represents the trace of the matrix,Representing the desire for the variable Σ, and solving the optimization problem by using alternating optimization, cauchy-Schwarz inequality and taylor expansion. Further, the statistical channel state information is obtained through user feedback, direct estimation of a base station or through an uplink detection signal. Further, the channel model, for the transmitter section, records the elevation angle and azimuth angle of the p-th transmission path as respectivelyAndIn the p-th transmit path, the propagation distance difference between the position t n＝(xn,yn)T of the n-th transmit fluid antenna and the origin t 0＝(0,0)T isThe signal phase difference between the nth transmitting fluid antenna and the origin in the p-th transmission path isWherein lambda is the signal wavelength, and the emission response vector is: The response matrix for all N transmit fluid antennas is: further, the channel model, for the receiver section, records the elevation angle and azimuth angle of the qth receiving path as AndIn the q-th reception path, the propagation distance difference between the position r m＝(xm,ym)T of the m-th reception fluid antenna and the origin r 0＝(0,0)T isThe signal phase difference between the mth receiving fluid antenna and the origin in th