CN116488691B

CN116488691B - Active IRS auxiliary MIMO (multiple input multiple output) sense-through integrated beam forming method

Info

Publication number: CN116488691B
Application number: CN202310202800.0A
Authority: CN
Inventors: 刘楠; 李进; 康维
Original assignee: Southeast University
Current assignee: Southeast University
Priority date: 2023-03-06
Filing date: 2023-03-06
Publication date: 2025-07-25
Anticipated expiration: 2043-03-06
Also published as: CN116488691A

Abstract

The present invention discloses an active IRS-assisted MIMO interaceptive integration beamforming method: Unlike a passive IRS, deploying an active IRS with an amplifier can overcome the multiplicative attenuation caused by IRS reflection. First, under the limits of base station transmit power and IRS transmit power, while meeting the transmission rate requirements of communication users, the present invention designs a beamforming algorithm to maximize the beam pattern in the direction of the IRS perception target. In this algorithm scenario, the base station only perceives the target through the IRS reflection link, but the communication user receives signals through the base station direct link and the IRS reflection link at the same time. The present invention can solve the problem of base station transmit beamforming design in active IRS-assisted MIMO interaceptive integration, while ensuring the transmission rate of the communication user, maximizing the beam pattern in the direction of the perception target, and compared with the passive IRS, the active IRS proposed in the present invention can greatly improve the performance of perception and communication.

Description

Active IRS auxiliary MIMO (multiple input multiple output) sense-through integrated beam forming method

Technical Field

The invention belongs to the technical field of wireless communication physical layers, relates to a communication perception integration technology, a MIMO (multiple input multiple output) beam forming technology and an active intelligent reconfigurable super-surface coverage enhancement technology, and particularly relates to a beam forming design problem of an active intelligent reconfigurable super-surface auxiliary MIMO sense integration system.

Background

The sense of general integration system is regarded as a key technology for alleviating the existing spectrum congestion in the 6G wireless network. In addition, the integrated communication system can bring better energy consumption and hardware efficiency with the unification of the radar system and the communication system compared with the conventional radar communication coexistence system. The perception task is typically considered with the help of a direct link between the base station and the sensing target. However, when the direct link is blocked by an obstacle such as a building, it is difficult for the base station to perceive the target. To address this problem, IRS acts as an effective auxiliary sensing technique that can create additional reflection-aware links between the base station and the target. However, product fading caused by passive IRSs will have a serious negative impact on IRS assisted ventilation integrated systems. In this case, if the path loss of the signal propagation environment is large, both the echo signal received by the base station and the signal received by the communication user are weak. Therefore, compared with a passive IRS, the active IRS provided with the active reflection amplifier can alleviate multiplicative fading, and the echo signal intensity of a base station end and the receiving signal intensity of a communication user are greatly improved. Aiming at the scene, the invention provides an iterative algorithm based on a minimum maximization technology and a semi-definite relaxation technology for solving the problem of active IRS auxiliary MIMO sense-through integrated beam forming.

Disclosure of Invention

The invention aims to provide an active IRS auxiliary MIMO sense-through integrated beam forming design method aiming at the defects in the prior art, which can meet the transmission rate requirement of communication users on one hand and maximize the beam pattern in the sense target direction on the other hand so as to improve the sense performance.

The technical scheme is that in order to achieve the aim of the invention, the invention adopts the following technical scheme:

an active IRS auxiliary MIMO sense-through integrated beam forming method comprises the following steps:

(1) Initializing a base station end beam forming vector w ⁽⁰⁾, an IRS end beam forming matrix E ⁽⁰⁾, a maximum iteration number upsilon _max and an iteration error epsilon, and enabling upsilon=0;

(2) Given an IRS end beam forming matrix E ^(υ), constructing an active IRS auxiliary sense-through integrated base station end beam forming sub-problem P1, and solving the problem P1 to obtain a base station end beam forming vector w ^(υ+1);

(3) Given a base station end beam forming vector w ^(υ+1), constructing an IRS end beam forming sub-problem P2 of an active IRS auxiliary sense-of-general integration, solving the sub-problem P2 without rank 1 constraint by adopting a CVX tool kit to obtain an IRS end beam forming matrix E ₁, and then constructing an IRS end beam forming matrix E ^(υ+1) meeting the rank 1 constraint by adopting Gaussian randomization;

(4) And (3) calculating the error of the iterative objective function, if the error is smaller than the iteration error E, stopping iteration, otherwise, returning to the step (2).

Preferably, the sub-problem P1 is constructed as:

R≥r,

Wherein, the Representing a general sense integrated beam forming matrix, N _T representing the number of transmitting antennas equipped by a base station, an active IRS having M reflecting elements and a reflection coefficient matrix represented asWherein the amplification gain constraint of the mth reflecting element is 0< |e _m|²≤p_max,p_max, the maximum amplification gain, and the channel between the base station and IRS is The target response matrix between the active IRS and the perceived target is represented as g=βa (θ) a ^H (θ), where θ is the angle of arrival/departure of the target relative to the IRS, β is the complex amplitude,Is the array steering vector of the IRS, where lambda is the wavelength,Is the spacing between the reflective elements, the communication rate of the user isR is the minimum rate requirement of the user, P ₀ is the maximum transmit power of the base station, and P ₁ is the maximum transmit power of the IRS.

Preferably, the minimization of the maximization technique sub-problem P1 is adopted:

(2.1) converting the problem P1 into an approximate sub-problem P3 of base station end beam forming of active IRS auxiliary sense integration:

s.t.2Re(w^(τ),HBw)-w^(τ),HBw^(τ)≥Ω₁,

Wherein, the The channel between IRS and user and the channel between base station and user isAnd Is the noise power;

(2.2) initializing the iteration number tau=0, the maximum iteration number tau _max, the maximum ratio transmit beamforming vector w ⁰, letting f (w ^(τ)) represent the objective function of the approximation sub-problem (P3), calculating f (w ⁽⁰⁾);

(2.3) a second step, given w ^τ, solving the approximate sub-problem (P3) by using a CVX tool kit to obtain w ^τ+1;

(2.4) let τ=τ+1;

(2.5) if Or τ > τ _max, stopping the iteration, otherwise, returning to (2.3).

Preferably, the IRS end beamforming sub-problem P2 is constructed as follows:

0<[diag(E₁)]_m≤p_max,1≤m≤M,

[diag(E₁)]_M+1=1,

E₁≥0,rank(E₁)=1.

Wherein, the And discarding the rank 1 constraint, wherein P2 is a convex problem, directly solving the convex problem through a CVX tool kit, and finally solving an IRS end beamforming matrix meeting the rank 1 constraint through Gaussian randomization.

Preferably, the specific steps of constructing the IRS end beamforming matrix E ^(υ+1) meeting the rank 1 constraint by using gaussian randomization include:

(3.1) decomposing the eigenvalue of the IRS end beamforming matrix E ₁ solved by the problem (P2) into E ₁＝UΣU^H, wherein each column of the matrix U is the eigenvector of the matrix E ₁, Σ is a diagonal matrix, and the diagonal element is the eigenvalue of the matrix E ₁;

(3.2) randomly generating 5000 candidate vectors

Wherein, the

(3.3) Selecting a rank 1 matrixSatisfy all constraints of the problem (P2) and maximize the objective function of the problem (P2) as the optimal solution E ^(υ+1), letIf h (w ^(υ+1),E^(υ+1))＜h(w^(υ+1),E^(υ)), returning to (3.2), otherwise, outputting the optimal IRS-end beam forming matrix E ^(υ+1).

Compared with the prior art, the method has the advantages that the problem of beam pattern maximization of the MIMO general sense integrated system under the limitation of the base station and the IRS transmitting power, the user communication speed and the reflection element amplification gain under the assistance of the active IRS is solved, the novel beam forming scheme is provided, the method is simple, the result is accurate, and compared with the existing passive IRS auxiliary MIMO general sense integrated system, the beam forming scheme can greatly improve the perception beam pattern, and further improve the perception performance under the requirement of ensuring communication service.

Drawings

Fig. 1 is a diagram of an active IRS auxiliary MIMO sense-all integrated system.

Detailed Description

The invention respectively considers the base station end beam forming sub-problem and the active IRS end beam forming sub-problem, specifically, the base station end transmitting power constraint is given, the active IRS transmitting power constraint is given, the beam pattern in the perception target direction is maximized, and the downlink communication user meets the transmission rate requirement. An iterative algorithm based on a minimum maximization technology and a semi-definite relaxation technology is provided, and a base station end beam forming vector and an active IRS end beam forming matrix obtained by the algorithm are both final beam forming schemes.

The method comprises the following specific steps:

Consider an active IRS-assisted MIMO system in which a DFRC base station is equipped with N _T transmit antennas and N _R receive antennas. Suppose a base station serves a single antenna communication user while perceiving a point target. For the perception task, it is assumed that the direct link between the perception target and the base station is blocked by an obstacle and a reflection-aware link is created with the assistance of the IRS. The active IRS has M reflective elements and the reflection coefficient matrix is expressed as Wherein the amplification gain constraint of the mth reflecting element is 0< |e _m|²≤p_max,p_max to the maximum amplification gain. The base station transmits DFRC signal of x=ws, wherein the vectorRepresenting the sense of general integrated beamforming matrix,Is a data symbol subject to complex gaussian distribution with zero mean and unit variance, i.eThus, the base station transmit power is

The channel between the base station and the IRS, the channel between the IRS and the user, and the channel between the base station and the user are respectively recorded asAndThe received signal of the communication user can be recorded asWherein, the AndIs an additive white gaussian noise caused by the amplifier of the active IRS and received at the user, which are respectively subject to complex gaussian distributionsAndHere, theAndIs the noise power. Thus, the communication user transmission rate can be expressed as

The amplified transmitted reflected signal at the active IRS used to sense the target may be expressed as

Y ₁＝E(H_BIx+n_I). Similarly, the amplified received reflected signal at the active IRS may be represented as y ₂＝E^H(GE(H_BIx+n_I)+n_p), where n _p is also an amplifier-induced additive Gaussian white noise independent of n _I and s, subject to complex Gaussian distribution Is the noise power. The distance between the active IRS and the perceived target is assumed to be so far that the target can be regarded as a point target. Thus, the target response matrix between the active IRS and the perceived target may be represented as g=βa (θ) a ^H (θ), where θ is the angle of arrival/departure of the target relative to the IRS, β is the complex magnitude,Is the array steering vector of the IRS, where lambda is the wavelength,Is the spacing between the reflective elements. Thus, the transmit beam pattern of the active IRS towards a given direction θ can be expressed asIn addition, the power of the amplified signal at the active IRS is

Thus, the overall optimization problem can be modeled as

R≥r,

|e_m|²≤p_max,1≤m≤M,

Where r is the minimum rate requirement of the user, P ₀ is the maximum transmit power of the base station, and P ₁ is the maximum transmit power of the IRS. To solve the overall optimization problem, an alternate optimization technique is used, comprising the steps of:

(1) Initializing a base station end beam forming vector w ⁽⁰⁾, an IRS end beam forming matrix E ⁽⁰⁾, a maximum iteration number upsilon _max and an iteration error epsilon, and enabling the iteration number upsilon=0;

(2) Giving an IRS end beam forming matrix E ^(υ), and solving an active IRS auxiliary sense-of-general integrated base station end beam forming sub-problem (P1) to obtain a base station end beam forming vector w ^(υ+1);

(3) Given a base station end beam forming vector w ^(υ+1), solving an IRS end beam forming sub-problem (P2) of active IRS auxiliary sense integration without rank 1 constraint by adopting a CVX tool kit to obtain an IRS end beam forming matrix E ₁, and then constructing the IRS end beam forming matrix E ^(υ+1) meeting the rank 1 constraint by adopting Gaussian randomization;

Preferably, the specific method for solving the problem (P1) in step (2) is as follows:

first, given the IRS-side beamforming matrix E, the problem (P1) can be constructed as

R≥r,

In order to solve the base station end beam forming optimization sub-problem (P1), a minimization and maximization technology is adopted, so that the base station end beam forming approximate sub-problem of the integrated auxiliary sense of active IRS can be defined as

s.t.2Re(w^(τ),HBw)-w^(τ),HBw^(τ)≥Ω₁,

Wherein, the

(2.1) Initializing the iteration number τ=0, the maximum iteration number τ _max, the maximum ratio transmit beamforming vector w ⁰, let f (w ^(τ)) represent the objective function of the problem (P3), and calculating f (w ⁽⁰⁾).

(2.2) Given w ^(τ), solving the problem (P3) using the CVX toolkit, yielding w ^(τ+1);

(2.3) let τ=τ+1;

(2.4) if Or τ > τ _max, stopping the iteration, otherwise, returning to (2.2).

Preferably, wherein step (3) comprises:

Given a base station side beamforming vector w, the IRS side beamforming sub-problem can be constructed as follows

R≥r,

|e_m|²≤p_max,1≤m≤M.

The optimization problem can be converted into by adopting the semi-definite relaxation technology

0<[diag(E₁)]_m≤p_max,1≤m≤M,

[diag(E₁)]_M+1=1,

E₁≥0,rank(E₁)=1.

(3.1) Decomposing the eigenvalue of the IRS end beamforming matrix E ₁ solved by the problem (P2) into E ₁＝UΣU^H, wherein each column of the matrix U is the eigenvector of the matrix E ₁, Σ is a diagonal matrix, and the diagonal element is the eigenvalue of the matrix E ₁.

(3.2) Randomly generating 5000 candidate vectors

Wherein, the

(3.3) Selecting a rank 1 matrixAll constraints of the problem (P2) are satisfied and the objective function of the problem (P2) is maximized as an optimal solution E ^(υ+1). Order theIf h (w ^(υ+1),E^(υ+1))＜h(w^(υ+1),E^(υ)), returning to (3.2), otherwise, outputting the optimal IRS-end beam forming matrix E ^(υ+1).

Claims

1. The method for forming the active IRS auxiliary MIMO communication integrated wave beam is characterized by comprising the following steps:

(2) Given an IRS end beam forming matrix E ^(υ), constructing an active IRS auxiliary sense-through integrated base station end beam forming sub-problem P1, and solving the sub-problem P1 to obtain a base station end beam forming vector w ^(υ+1);

(4) Calculating the error of the iterative objective function, if the error is smaller than the iteration error E, stopping iteration, otherwise, returning to the step (2);

The sub-problem P1 is constructed as:

Wherein, the Representing a general sense integrated beam forming matrix, N _T representing the number of transmitting antennas equipped by a base station, an active IRS having M reflecting elements and a reflection coefficient matrix represented asWherein the amplification gain constraint of the mth reflecting element is 0< |e _m|²≤p_max,p_max, the maximum amplification gain, and the channel between the base station and IRS is The target response matrix between the active IRS and the perceived target is represented as g=βa (θ) a ^H (θ), where θ is the angle of arrival/departure of the target relative to the IRS, β is the complex amplitude,Is the array steering vector of the IRS, where lambda is the wavelength,Is the spacing between the reflective elements, the communication rate of the user isR is the minimum rate requirement of the user, P ₀ is the maximum transmission power of the base station, and P ₁ is the maximum transmission power of the IRS;

The IRS end beam forming sub-problem P2 is constructed as follows:

Wherein, the

Discarding the rank 1 constraint, solving P2 as a convex problem through a CVX tool kit, and finally solving an IRS end beamforming matrix meeting the rank 1 constraint through Gaussian randomization.

2. The method for forming a beam by integrating active IRS-assisted MIMO communication and as set forth in claim 1, wherein the minimizing and maximizing technique sub-problem P1 is adopted, and the specific steps include:

(2.1) converting the sub-problem P1 into an active IRS auxiliary sense-of-general integrated base station end beam forming approximate sub-problem P3:

Wherein, the The channel between IRS and user and the channel between base station and user isAndIs the noise power;

(2.2) initializing the iteration number τ=0, the maximum iteration number τ _max, the maximum ratio transmit beamforming vector w ⁽⁰⁾, let f (w ^(τ)) represent the objective function of the approximation sub-problem P3, and calculating f (w ⁽⁰⁾);

(2.3) a second step, given w ^(τ), solving the approximate sub-problem P3 by using a CVX tool kit to obtain w ^(τ+1);

(2.4) let τ=τ+1;

3. The method for forming an integrated beam forming of an active IRS auxiliary MIMO passband as claimed in claim 1, wherein the specific step of constructing an IRS end beam forming matrix E ^(υ+1) satisfying rank 1 constraint by gaussian randomization comprises:

(3.1) decomposing the eigenvalue of the IRS end beamforming matrix E ₁ solved by the sub-problem P2 into E ₁＝UΣU^H, wherein each column of the matrix U is the eigenvector of the matrix E ₁, Σ is a diagonal matrix, and the diagonal element is the eigenvalue of the matrix E ₁;

(3.2) randomly generating 5000 candidate vectors Wherein, the

(3.3) Selecting a rank 1 matrixSatisfies all constraints of the sub-problem P2, maximizes the objective function of the sub-problem P2 as the optimal solution E ^(υ+1), makesIf h (w ^(υ+1),E^(υ+1))＜h(w^(υ+1),E^(υ)), returning to (3.2), otherwise, outputting the optimal IRS-end beam forming matrix E ^(υ+1).