A joint beamforming and deployment method for dual-intelligent reflecting surface assisted communication

Abstract

This invention discloses a joint beamforming and deployment method for dual-intelligent reflector-assisted communication, comprising the following steps: S1, inputting the location information of the deployment area and the target area; S2, calculating and configuring the phase and power of the transmitted signal at the access point; S3, constructing and decomposing the joint beamforming and deployment problem of the intelligent reflectors; S4, for a given arbitrary intelligent reflector deployment, calculating the phase shift of the passive reflector elements of the intelligent reflectors; S5, based on the phase shift of the passive reflector elements of the intelligent reflectors described in S4, calculating and deploying the intelligent reflector deployment position; S6, based on the intelligent reflector deployment position described in S5, calculating and configuring the phase shift of the passive reflector elements of the intelligent reflectors. The joint beamforming and deployment method for dual-intelligent reflector-assisted communication proposed in this invention can significantly improve the communication coverage and the worst signal-to-noise ratio at the edge of the target area, while avoiding the overhead of channel estimation.

Description

Technical Field

[0001] This invention relates to the field of digital wireless communication technology, and specifically to a joint beamforming and deployment method for dual-intelligent reflector-assisted communication. Background Technology

[0002] To further improve the data transmission rate and communication coverage of 5G and future 6G wireless network systems, industry and academia are exploring more cost-effective and competitive physical layer technologies. However, existing technologies suffer from high energy consumption, high channel estimation overhead, severe noise interference, and high cost of covering the target area due to the large number of active antennas.

[0003] Currently, among the candidate technologies for 6G, smart reflectors (also known as reconfigurable smart surfaces) stand out due to their unique characteristics such as low cost, low power consumption, programmability, easy deployment, and noiselessness. By introducing wireless networks, smart reflectors transform the wireless propagation environment from passive adaptation to active control, thereby constructing an intelligent wireless environment. Smart reflectors are a promising wireless channel reconfiguration technology that brings a new paradigm to the coverage design of future networks, meeting the needs of future mobile communications.

[0004] Beamforming is a technique that uses beamformers to control the phase and signal amplitude of each transmitter, thereby obtaining the desired phase shift and destructive interference patterns at the receiver. Signals received by different receivers are combined in an appropriate manner to achieve the desired signal radiation pattern. In smart reflector-assisted wireless systems, when the line-of-sight channel between the transmitter and receiver is blocked, using beamforming at the transmitter can improve the antenna gain from the transmitter to the smart reflector. Summary of the Invention

[0005] The purpose of this invention is to overcome the above-mentioned defects in the prior art and provide a joint beamforming and deployment method for dual intelligent reflector-assisted communication, which has the advantages of low cost, low complexity and wide communication coverage.

[0006] The objective of this invention can be achieved by adopting the following technical solutions:

[0007] A joint beamforming and deployment method for dual-intelligent reflector-assisted communication is disclosed, applied to a wireless communication system with dual-intelligent reflector assistance. This wireless communication system includes at least one access point with M antennas and two access points with N antennas. I One passive reflector unit with an intelligent reflective surface, two intelligent reflective surface controllers, and one deployment area. and 1 target area The joint beamforming and deployment method includes the following steps:

[0008] S1, Input Deployment Area and target area Location information;

[0009] S2. Calculate and configure the phase and transmission power of the access point's transmitted signal;

[0010] S3. Construct and decompose the problem of intelligent reflector joint beamforming and deployment;

[0011] S4. For a given arbitrary smart reflector deployment, calculate the phase shift of the passive reflector unit of the smart reflector.

[0012] S5. Based on the phase shift of the passive reflection unit of the intelligent reflective surface, calculate and deploy the intelligent reflective surface deployment position;

[0013] S6. Based on the deployment location of the intelligent reflective surface, calculate and configure the phase shift of the passive reflective unit of the intelligent reflective surface.

[0014] Further, step S1 is as follows:

[0015] Enter the following information about the deployment region. and target area Location information:

[0016] Assuming all location information is based on a three-dimensional Cartesian coordinate system with x, y, and z axes, and the height of each smart reflector is represented by H, the deployment area... The length is represented by R x Deployment area The horizontal distance between the x-axis and the x-axis is represented by D > 0, and the deployment area is... The horizontal distance between the midpoint and the y-axis is denoted as c0, and the deployment area is... The midpoint of the xy plane is denoted as r. c =[c0, D] T The reference point of the k-th intelligent reflective surface in the xy plane is denoted as... The reference point of the k-th intelligent reflective surface in three-dimensional space is represented as: Where k∈{1,2}, and the superscript (·) T Defined as the transpose operation;

[0017] target area The length is represented as D x Target area The width is represented as D y Target area The position in three-dimensional space is represented as target area The position in the xy plane is represented as d = [d x d y ] T ,in,

[0018] Furthermore, step S2 is as follows:

[0019] The one-dimensional steering vector function is defined as: Where ζ is defined as the phase difference between signals arriving or transmitted from two adjacent antennas or passive reflectors, and N t Defined as the size of a uniform linear array.

[0020] The wavelength of the transmitted signal is denoted by λ, and the distance between two adjacent passive reflective elements is denoted by Ψ. I The number of passive reflective elements along the x-axis and z-axis of each smart reflective surface is represented by N. x and N z The elevation angle and azimuth angle of arrival from the access point to the k-th intelligent reflector are respectively denoted as φ. R，k (r k ) and η R，k (r k The receiving array response of the k-th smart reflector is expressed as:

[0021]

[0022] Where, k∈{1,2}, Indicates the Kronecker product. For about φ R，k (r k ) and η R，k (r k Spatial frequency along the x-axis dimension, For about η R，k (r k Spatial frequency along the z-axis dimension;

[0023] Let ||||| be the space of a×b complex matrices, and ||·|| be the 2-norm operation, with the superscript (·). H Defined as the conjugate transpose operation. Defined as from the access point to the deployment area The transmission array response, ||a T (r c )|| 2 =M; The far-field line-of-sight channel from the access point to the k-th smart reflector is represented as: Wherein, β0 is defined as the channel gain at a reference distance of 1 meter. Defined as the distance from the access point to the k-th smart reflective surface;

[0024] The k-th intelligent reflective surface to the target area Position in the xy plane The launch elevation angle and launch azimuth angle are respectively expressed as φ T，k (r k ,d) and η T，k (r k ,d); the reflection array response of the k-th smart reflective surface is expressed as: in, Defined as about φ T，k (r k ,d) and η T，k (r k d) Spatial frequency along the x-axis dimension Defined as about φ T，k (r k d) Spatial frequency along the z-axis; the k-th intelligent reflective surface to the target area Position in the xy plane The far-field line-of-sight channel is represented as:

[0025]

[0026] in, Defined as the distance from the k-th intelligent reflective surface to the target area Position in the xy plane The distance;

[0027] diag(x) is defined as a diagonal matrix where each diagonal element is a corresponding element in x. Let n be the phase shift of the nth passive reflective element in the kth smart reflective surface, and let the reflection phase shift matrix of the kth smart reflective surface be expressed as: Defined as the phase shift vector of the passive reflective element of the k-th smart reflector; the transmission beamforming vector of the access point is expressed as... ||v|| = 1; Target region Position in the xy plane The received signal is represented as:

[0028]

[0029] in, P t Let be the transmit power of the access point, x be the transmitted signal of the access point, and n0 be the signal with zero mean and variance. Additive white Gaussian noise;

[0030] c * The superscript indicates the optimal value of variable c; in a given deployment area and target area Based on the location information and the maximum ratio transmission theory, in order to ensure that the target area... The optimal transmission beamforming vector at the access point, where the received signal energy is at its maximum, is expressed as:

[0031]

[0032] According to the optimal transmission beamforming vector v * and the transmit power P of the access point t The beamforming controller at the access point sets the phase and transmit power of the transmitted signal.

[0033] Furthermore, step S3 is as follows:

[0034] S3.1, The problem of intelligent reflector joint beamforming and deployment is defined as follows:

[0035] For the target area Position in the xy plane The signal-to-noise ratio is expressed as:

[0036]

[0037] in, Defined as an approximately negligible cross term. The above equation reflects that the mutual interference between the beams generated by the two smart reflectors can be approximately ignored. Therefore, the original joint beamforming and deployment of the two smart reflectors can be simplified to optimizing the joint beamforming and deployment of each individual smart reflector.

[0038] Based on the above formula, two smart reflective surfaces are used to cover the two surfaces respectively. Two equally divided sub-target regions and Right now This simplifies the dual-smart reflector joint beamforming and deployment to a single-smart reflector joint beamforming and deployment; st is defined as constrained by max x f(x) is defined as maximizing the objective function f(x), min x f(x) is defined as minimizing the objective function f(x); therefore, the problem of joint beamforming and deployment of smart reflectors is expressed as:

[0039]

[0040]

[0041]

[0042] in, Corresponding access point to target sub-region Array gain at the receiving point Corresponding access point to target sub-region Multiplicative distance path loss at the receiving point;

[0043] S3.2. The above-mentioned intelligent reflector joint beamforming and deployment problem is broken down into two sub-problems: 1) the intelligent reflector phase shift optimization problem and 2) the intelligent reflector deployment optimization problem, as follows:

[0044] Since the aforementioned problem of intelligent reflector joint beamforming and deployment remains difficult to solve using standard optimization algorithms, and because the phase shift optimization of intelligent reflectors is similar to the design of analog beamforming or phased arrays, the original problem is decomposed into two sub-problems: 1) intelligent reflector phase shift optimization problem and 2) intelligent reflector deployment optimization problem. These two sub-problems are then solved step-by-step to obtain a lower bound on the optimal solution to the aforementioned intelligent reflector joint beamforming and deployment problem. The first intelligent reflector phase shift optimization problem is expressed as: In this problem, for any given smart reflective surface deployment r k Phase optimization of the intelligent reflective surface should be optimized to ensure that the reflection is effective in the sub-target region. The worst-case array gain is maximized in the given location; the second smart reflector deployment optimization problem is expressed as: in, Defined as the phase shift vector of the passive reflection unit of the intelligent reflector obtained after solving the above-mentioned intelligent reflector phase shift optimization problem.

[0045] Furthermore, step S4 is as follows:

[0046] S4.1 By dividing the k-th intelligent reflector into multiple sub-arrays, the coverage bandwidth of the k-th intelligent reflector is made greater than that of the corresponding target sub-region. The required waveform width is determined as follows:

[0047] First, by utilizing the concept of array clusters, N I The beam is divided into L equal-sized subarrays, with the beam pointing in a direction sufficient for space. Each subarray has N... s =N I / L reflective units; the spatial frequency direction pointed to by the sub-beams of the cluster of the l-th sub-array of the k-th smart reflective surface is represented as Where, φ k，l and η k，lLet be the elevation and azimuth angles of the l-th subarray of the k-th smart reflector, respectively; and let α be the common phase coefficient of the l-th subarray of the k-th smart reflector. k，l Each set of intelligent reflective surface subarrays is represented as Each set of intelligent reflective surface subarrays is represented as: The coverage bandwidth of the L subarrays of each smart reflector is represented by Ω. L (L), covering the target area The required angle range is expressed as in, Defined as the target area to be covered Minimum required angle Defined as the target area to be covered The maximum required angle; by dividing the k-th smart reflector into multiple sub-arrays, the coverage width of the k-th smart reflector is greater than that of the corresponding target sub-region. The required wavewidth is specifically expressed as: As can be seen from the above equation, the number of subarrays L is directly proportional to the coverage bandwidth of the smart reflector.

[0048] S4.2, Set the set of spatial frequency directions pointed to by the sub-beams of the cluster of the l-th subarray of the k-th smart reflector. The set of common phase coefficients of the k-th smart reflector and the l-th subarray. Make the array gain of the k-th smart reflector in the corresponding target region The inner approximate equality is determined as follows:

[0049] Set spatial frequency interval The coverage wavelength for each subarray is defined by the spatial frequency resolution of the subarray. They are separated; therefore, the spatial frequency directions of the subarrays of the first and second smart reflectors are represented as follows: Where, Φ 1，1 and Φ 2，1 These are defined as the starting spatial frequency directions of the first and second smart reflective surfaces, respectively.

[0050] Because when the spatial frequency direction Φ of the sub-beam of the l-th sub-array of the k-th smart reflector is pointed to... k，l The intersection point Ω of the adjacent subarrays of the k-th smart reflector is equal to the intersection point of the adjacent subarrays. k At that time, the resulting array gain is mainly contributed by the l-th subarray of the k-th smart reflector, while for Φ k，L ≠Ω k The array gain produced by the beams of other subarrays is so small as to be negligible; the intersection point of the adjacent subarrays of the k-th smart reflector is denoted as Ω. k，tLet t = 1, ..., L-1, and the intersection point between the first and second intelligent reflective surfaces be denoted as... Therefore, to flatten the beam gain generated by the intersection points of all adjacent subarrays of the k-th smart reflector, the intersection point Ω of the adjacent subarrays of the k-th smart reflector... k，t The intersection points between t=1,...,L-1 and the first and second smart reflective surfaces. The phases at all points should be the same, specifically expressed as:

[0051]

[0052] The above equations result in the beam gain of the beamforming of the dual intelligent reflectors being within the target region. They are approximately equal in all positions;

[0053] According to the above formula, the common phase coefficient α of the l-th subarray of the k-th smart reflector is... k，l Set to:

[0054]

[0055] in, and

[0056] S4.3 Setting the optimal number of subarrays L * (r k ) and the number of passive reflective elements in the subarray The process for solving the phase shift of the passive reflective element of the k-th smart reflective surface is as follows:

[0057] First, according to the settings in steps S4.2 and S4.3, Because, therefore, the optimal number of subarrays and the number of passive reflection units in the subarrays are expressed as:

[0058]

[0059] The initial spatial frequency directions of the first and second smart reflective surfaces are respectively represented as:

[0060]

[0061] Based on the above L * (r k ),as well as The optimal spatial frequency direction and common phase coefficient of the intelligent reflector are expressed as follows:

[0062]

[0063]

[0064] in, and Based on the above and The phase shift of the nth passive reflective element of the kth smart reflective surface is expressed as:

[0065]

[0066] Furthermore, step S5 is as follows:

[0067] Based on the phase shift of the passive reflective unit of the smart reflective surface described in step S4, the worst-case array gain is expressed as:

[0068] Combining the above equations, the aforementioned intelligent reflective surface deployment optimization problem can be rewritten as:

[0069]

[0070] Because in the above-mentioned intelligent reflector deployment optimization problem, the intelligent reflector deployment optimization only relates to the variables... Therefore, the aforementioned problem of optimizing the deployment of intelligent reflective surfaces can be further simplified to a problem concerning... Single-variable optimization problem: in, From the objective function of the above problem, it can be seen that reducing the coverage target area is... Required angle range Multiplicative distance path loss can increase the worst-case signal-to-noise ratio; based on the location of the intelligent reflector obtained by the one-dimensional search algorithm, dual intelligent reflectors are deployed in the deployment area.

[0071] Furthermore, the process of step S6 is as follows:

[0072] Substituting the deployment location of the smart reflector described in step S5 into the following formula, we can obtain the phase shift of the nth passive reflective unit of the smart reflector:

[0073]

[0074] According to the above formula, each smart reflector controller sets the phase shift of the passive reflective unit of each smart reflector.

[0075] The present invention has the following advantages and effects compared with the prior art:

[0076] 1) The present invention proposes a joint beamforming and deployment method for dual intelligent reflector-assisted communication. By deploying dual intelligent reflectors in a distributed manner to cover the target area / communication blind zone, this method avoids the high cost and high energy consumption problems caused by traditional receiving radio frequency links, greatly reduces cost and energy consumption, and significantly improves the communication coverage and the worst signal-to-noise ratio at the edge of the target area.

[0077] 2) This invention proposes a joint beamforming and deployment method for dual intelligent reflector-assisted communication. It does not require channel estimation overhead and only needs the geographical location information of the deployment area and the target area. Compared with existing methods, this method avoids the performance degradation caused by channel training overhead, thereby improving the efficiency and throughput of the communication system.

[0078] 3) The joint beamforming and deployment method for dual intelligent reflector-assisted communication proposed in this invention is a closed-form solution that does not require iterative calculations, greatly reducing computational complexity and meeting the real-time processing requirements of communication systems. Attached Figure Description

[0079] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this application, illustrate exemplary embodiments of the invention and, together with their description, serve to explain the invention and do not constitute an undue limitation thereof. In the drawings:

[0080] Figure 1 This is a model diagram of a wireless downlink communication system assisted by dual intelligent reflectors in an embodiment of the present invention;

[0081] Figure 2 This is a flowchart of a joint beamforming and deployment method for dual-intelligent reflector-assisted communication according to the present invention;

[0082] Figure 3 This is a performance comparison simulation diagram from Embodiment 1 of the present invention;

[0083] Figure 4 This is a performance comparison simulation diagram from Embodiment 2 of the present invention;

[0084] Figure 5 This is a performance comparison simulation diagram from Embodiment 3 of the present invention. Detailed Implementation

[0085] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0086] Please see Figure 1 , Figure 1 This is a model diagram of a dual-intelligent reflector-assisted wireless downlink communication system according to all embodiments of the present invention. The wireless communication system includes at least one access point with M antennas, and two access points with N antennas. I One passive reflector unit with an intelligent reflective surface, two intelligent reflective surface controllers, and one deployment area. and 1 target area

[0087] To illustrate the technological advancements of this invention, the joint beamforming and deployment method based on dual intelligent reflector-assisted communication proposed in this invention was compared with other methods in different embodiments on the MATLAB platform, highlighting the worst-case signal-to-noise ratio performance. These other methods included: 1) a centralized benchmark method with N = 2*N. I The intelligent reflector of the passive reflector unit is optimized according to the proposed joint beamforming and deployment method of dual intelligent reflector-assisted communication. The beamforming and deployment of the intelligent reflector are combined with the 2) distributed benchmark method: two N are fixed respectively. I The intelligent reflective surfaces of each reflective unit are located at the midpoint of each sub-region. Then, the beamforming of the dual intelligent reflective surfaces is optimized using the proposed joint beamforming and deployment method for dual intelligent reflective surface-assisted communication.

[0088] Example 1

[0089] In this embodiment 1, the specific parameter settings are as follows:

[0090] Assume all location information is based on a three-dimensional Cartesian coordinate system with x, y, and z axes, and the access point is located at the origin. Other parameter settings are as follows: the transmission power P of the access point... t =5dBm, target area Length D x =10m, deployment area Length R x =10m, deployment area The horizontal distance between the x-axis and the x-axis is D = 5m, and the deployment area is... At the midpoint r of the xy plane c =[c0, D] T =[85, 5] T m, the variance of additive white Gaussian noise The channel gain β0 at a reference distance of 1 meter is -30dB, and the number of passive reflective elements N of the smart reflector is... I =315, number of antennas at the access point M=64, wavelength of the transmitted signal λ=0.125m, spacing between two adjacent antennas and the spacing between two adjacent passive reflective units

[0091] The following is combined with Figure 1 and Figure 2 The following describes the process steps of a combined beamforming and deployment method for dual intelligent reflector-assisted communication disclosed in Embodiment 1.

[0092] In this embodiment 1, step S1 is specifically implemented as follows:

[0093] You need to enter the following information about the deployment region. and target area Location information:

[0094] The height of each smart reflective surface is denoted by H, and the deployment area is... The length is represented by R x Deployment area The horizontal distance between the x-axis and the x-axis is represented by D > 0, and the deployment area is... The horizontal distance between the midpoint and the y-axis is denoted as c0, and the deployment area is... The midpoint of the xy plane is denoted as r. c =[c0, D] T The reference point of the k-th intelligent reflective surface in the xy plane is denoted as... The reference point of the k-th intelligent reflective surface in three-dimensional space is represented as: Where k∈{1,2}, and the superscript (·) T Defined as the transpose operation.

[0095] target area The length is represented as D x Target area The width is represented as D y Target area The position in three-dimensional space is represented as target area The position in the xy plane is represented as d = [d x d y ] T ,in,

[0096] In this embodiment 1, step S2 is specifically implemented as follows:

[0097] The one-dimensional steering vector function is defined as: Where ζ is defined as the phase difference between signals arriving or transmitted from two adjacent antennas or passive reflectors, and N t Defined as the size of a uniform linear array.

[0098] The wavelength of the transmitted signal is denoted by λ, and the distance between two adjacent passive reflective elements is denoted by Ψ. I The number of passive reflective elements along the x-axis and z-axis of each smart reflective surface is represented by N. x and N z The elevation angle and azimuth angle of arrival from the access point to the k-th intelligent reflector are respectively denoted as φ. R，k (r k ) and η R，k (r k The receiving array response of the k-th smart reflector is expressed as:

[0099]

[0100] Where, k∈{1,2}, Indicates the Kronecker product. For about φ R，k (r k ) and η R，k (r k Spatial frequency along the x-axis dimension, For about η R，k (r k Spatial frequency along the z-axis dimension;

[0101] Let ||||| be the space of a×b complex matrices, and ||·|| be the 2-norm operation, with the superscript (·). H Defined as the conjugate transpose operation. Defined as from the access point to the deployment area The transmission array response, ||a T (r c )|| 2 =M; The far-field line-of-sight channel from the access point to the k-th smart reflector is represented as: Wherein, β0 is defined as the channel gain at a reference distance of 1 meter. Defined as the distance from the access point to the k-th smart reflective surface;

[0102] The k-th intelligent reflective surface to the target area Position in the xy plane The launch elevation angle and launch azimuth angle are respectively expressed as φ T，k (r k ,d) and η T，k (r k ,d); the reflection array response of the k-th smart reflective surface is expressed as: in, Defined as about φT，k (r k ,d) and η T，k (r k d) Spatial frequency along the x-axis dimension Defined as about φ T，k (r k d) Spatial frequency along the z-axis; the k-th intelligent reflective surface to the target area Position in the xy plane The far-field line-of-sight channel is represented as:

[0103]

[0104] in, Defined as the distance from the k-th intelligent reflective surface to the target area Position in the xy plane The distance;

[0105] diag(x) is defined as a diagonal matrix where each diagonal element is a corresponding element in x. Let n be the phase shift of the nth passive reflective element in the kth smart reflective surface, and let the reflection phase shift matrix of the kth smart reflective surface be expressed as: Defined as the phase shift vector of the passive reflective element of the k-th smart reflector; the transmission beamforming vector of the access point is expressed as... ||v|| = 1; Target region Position in the xy plane The received signal is represented as:

[0106]

[0107] in, P t Let be the transmit power of the access point, x be the transmitted signal of the access point, and n0 be the signal with zero mean and variance. Additive white Gaussian noise;

[0108] c * The superscript indicates the optimal value of variable c; in a given deployment area and target area Given the location information, according to the maximum ratio transmission theory, the optimal transmission beamforming vector of the access point is expressed as:

[0109]

[0110] According to the optimal transmission beamforming vector v * and the transmit power P of the access point t The beamforming controller at the access point sets the phase and transmit power of the transmitted signal.

[0111] In this embodiment 1, step S3 is specifically implemented as follows:

[0112] S3.1, The problem of intelligent reflector joint beamforming and deployment is defined as follows:

[0113] For the target area Position in the xy plane The signal-to-noise ratio is expressed as:

[0114]

[0115] in, Defined as an approximately negligible cross term.

[0116] Based on the above formula, two smart reflective surfaces are used to cover the two surfaces respectively. Two equally divided sub-target regions and Right now This simplifies the dual-smart reflector joint beamforming and deployment to a single-smart reflector joint beamforming and deployment; st is defined as constrained by max x f(x) is defined as maximizing the objective function f(x), min x f(x) is defined as minimizing the objective function f(x); therefore, the problem of joint beamforming and deployment of smart reflectors is expressed as:

[0117]

[0118]

[0119]

[0120] in, Corresponding access point to target sub-region Array gain at the receiving point Corresponding access point to target sub-region Multiplicative distance path loss at the receiving point;

[0121] S3.2. The above-mentioned intelligent reflector joint beamforming and deployment problem is broken down into two sub-problems: 1) the intelligent reflector phase shift optimization problem and 2) the intelligent reflector deployment optimization problem, as follows:

[0122] By decomposing the aforementioned smart reflector joint beamforming and deployment problem into two sub-problems: 1) the smart reflector phase shift optimization problem and 2) the smart reflector deployment optimization problem, a lower bound on the optimal solution of the aforementioned smart reflector joint beamforming and deployment problem is obtained; the first smart reflector phase shift optimization problem is expressed as: The second intelligent reflective surface deployment optimization problem is expressed as: in, Defined as the phase shift vector of the passive reflection unit of the intelligent reflector obtained after solving the above-mentioned intelligent reflector phase shift optimization problem.

[0123] In this embodiment 1, step S4 is specifically implemented as follows:

[0124] S4.1 By dividing the k-th intelligent reflector into multiple sub-arrays, the coverage bandwidth of the k-th intelligent reflector is made greater than that of the corresponding target sub-region. The required waveform width is determined as follows:

[0125] First, let N I The beam is divided into L equal-sized subarrays, with the beam pointing in a direction sufficient for space. Each subarray has N... s =N I / L reflective units; the spatial frequency direction pointed to by the sub-beams of the cluster of the l-th sub-array of the k-th smart reflective surface is represented as Where, φ k，l and η k，l Let be the elevation and azimuth angles of the l-th subarray of the k-th smart reflector, respectively; and let α be the common phase coefficient of the l-th subarray of the k-th smart reflector. k，l Each set of intelligent reflective surface subarrays is represented as Each set of intelligent reflective surface subarrays is represented as: The coverage bandwidth of the L subarrays of each smart reflector is represented by Ω. L (L), covering the target area The required angle range is expressed as in, Defined as the target area to be covered Minimum required angle Defined as the target area to be covered The maximum required angle; by dividing the k-th smart reflector into multiple sub-arrays, the coverage width of the k-th smart reflector is greater than that of the corresponding target sub-region. The required wavewidth is specifically expressed as:

[0126]

[0127] S4.2, Set the set of spatial frequency directions pointed to by the sub-beams of the cluster of the l-th subarray of the k-th smart reflector. The set of common phase coefficients of the k-th smart reflector and the l-th subarray. Make the array gain of the k-th smart reflector in the corresponding target region The inner approximate equality is determined as follows:

[0128] Set spatial frequency interval The coverage wavelength for each subarray is defined by the spatial frequency resolution of the subarray. They are separated; therefore, the spatial frequency directions of the subarrays of the first and second smart reflectors are represented as follows:

[0129]

[0130] Where, Φ 1，1 and Φ 2，1 The starting spatial frequency directions of the first and second smart reflectors are defined respectively; the intersection point of adjacent subarrays of the k-th smart reflector is denoted as Ω. k，t Let t = 1, ..., L-1, and the intersection point between the first and second intelligent reflective surfaces be denoted as... To flatten the beam gain generated by the intersection points of all adjacent subarrays of the k-th smart reflector, the intersection point Ω of the adjacent subarrays of the k-th smart reflector... k，t The intersection points between t=1,...,L-1 and the first and second smart reflective surfaces. The phases at all points should be the same, specifically expressed as:

[0131]

[0132] According to the above formula, the common phase coefficient α of the l-th subarray of the k-th smart reflector is... k，l Set to:

[0133]

[0134] in, and

[0135] S4.3 Setting the optimal number of subarrays L * (r k ) and the number of passive reflective elements in the subarray The process for solving the phase shift of the passive reflective element of the k-th smart reflective surface is as follows:

[0136] First, according to the settings in steps S4.2 and S4.3, Therefore, the optimal number of subarrays and the optimal number of passive reflective elements in the subarrays are expressed as follows:

[0137]

[0138] The initial spatial frequency directions of the first and second smart reflective surfaces are respectively represented as:

[0139]

[0140] Based on the above L * (r k ),as well as The optimal spatial frequency direction and common phase coefficient of the intelligent reflector are expressed as follows:

[0141]

[0142]

[0143] in, and Based on the above and The phase shift of the nth passive reflective element of the kth smart reflective surface is expressed as:

[0144]

[0145] In this embodiment 1, step S5 is specifically implemented as follows:

[0146] Based on the phase shift of the passive reflective unit of the smart reflective surface described in step S4, the worst-case array gain is expressed as:

[0147]

[0148] Combining the above equations, the aforementioned intelligent reflective surface deployment optimization problem can be rewritten as:

[0149]

[0150] The aforementioned optimization problem for the deployment of intelligent reflective surfaces can be further simplified to: Single-variable optimization problem:

[0151]

[0152]

[0153] in, Then, based on the location of the intelligent reflective surface obtained by the one-dimensional search algorithm, the dual intelligent reflective surfaces are deployed in the deployment area.

[0154] In this embodiment 1, step S6 is specifically implemented as follows:

[0155] Substituting the deployment location of the smart reflector described in step S5 into the following formula, we can obtain the phase shift of the nth passive reflective unit of the smart reflector:

[0156]

[0157] According to the above formula, each smart reflector controller sets the phase shift of the passive reflective unit of each smart reflector.

[0158] like Figure 3 As shown, Figure 3 The target area was drawn. The relationship between signal-to-noise ratio (SNR) and user location. The worst-case SNR of the method in this embodiment is significantly better than that of the centralized and distributed benchmark methods. Furthermore, in terms of minimum SNR, the method in this embodiment achieves a gain of up to 2.1 dB compared to the centralized benchmark method. This is because, after adopting the method in this embodiment, the target area... User locations at the edge can obtain higher passive beamforming gain from their nearest distributed smart reflector.

[0159] Example 2

[0160] In this embodiment 2, the specific parameter settings are as follows:

[0161] Assume all location information is based on a three-dimensional Cartesian coordinate system with x, y, and z axes. Target area. Length D x The m spans are 5m, 7m, 9m, 11m, 13m, and 15m respectively; deployment area At the midpoint r of the xy plane c =[c0, D] T =[80+D x / 2,5] T m. For other parameter settings, please refer to Example 1.

[0162] In this embodiment 2, each time the target area is... Length D x After obtaining the value, the relationship with the target area is changed. Length D x The relevant variables are determined, and steps S1-S6 are performed once, wherein steps S1-S6 are referred to in Example 1.

[0163] like Figure 4 As shown, Figure 4 The worst signal-to-noise ratio and target area are shown. Length Dx The relationship between them. First, the method of the present invention significantly outperforms the centralized benchmark method in terms of worst signal-to-noise ratio, and its performance gain increases with the target area. Length D x It increases with the increase of the target area. Length D x The increase in the centralized reference method, in the target area, is due to the centralized intelligent reflective surface. The edges suffer higher multiplicative distance path loss; conversely, by dividing the smart reflective surface with N passive reflective units into two separate reflective surfaces with N passive reflective units... I The distributed intelligent reflective surface of the passive reflective unit can significantly improve the worst-case signal-to-noise ratio because it can reduce the coverage target area. The required angular range and multiplicative distance path loss. Therefore, at a given signal-to-noise ratio threshold, the method of this embodiment outperforms the centralized and distributed benchmark methods in terms of coverage performance, especially for wide coverage areas. Second, the method of this embodiment significantly outperforms the distributed benchmark method, demonstrating the importance of optimizing smart reflector deployment.

[0164] Example 3

[0165] In this embodiment 3, the specific parameter settings are as follows:

[0166] Assume all positional information is based on a three-dimensional Cartesian coordinate system with x, y, and z axes. The number of passive reflective units N in the intelligent reflective surface. I Take 150, 200, 250, 300, 350, and 400 samples respectively. For other parameter settings, please refer to Example 1.

[0167] In this embodiment 3, the number N of passive reflective units on the intelligent reflective surface each time is... I After taking the value, the number N of passive reflective units of the smart reflective surface is changed. I The relevant variables are determined, and steps S1-S6 are performed once, wherein steps S1-S6 are referred to in Example 1.

[0168] like Figure 5 As shown, Figure 5 A graph showing the relationship between the worst signal-to-noise ratio (SNR) and passive reflective elements was plotted. The method of this embodiment achieves a higher worst SNR than the centralized and distributed benchmark methods. This is because, at the worst SNR location, the method of this embodiment has less multiplicative distance path loss compared to the centralized and distributed benchmark methods, which helps to provide a stronger beam to cover the target area. For example, to achieve a target signal-to-noise ratio of 18 dB, the method of this embodiment requires approximately 475 passive reflective elements, while the centralized and distributed benchmark methods both require approximately 650 more passive reflective elements. This example illustrates the importance of using a flexible, distributed smart reflector deployment approach to maximize smart reflector-assisted communication coverage.

[0169] In summary, the joint beamforming and deployment method for dual-intelligent reflector-assisted communication proposed in this invention can significantly improve the communication coverage and the worst signal-to-noise ratio at the edge of the target area, while avoiding the overhead of channel estimation.

[0170] The above embodiments are preferred embodiments of the present invention, but the embodiments of the present invention are not limited to the above embodiments. Any changes, modifications, substitutions, combinations, or simplifications made without departing from the spirit and principle of the present invention shall be considered equivalent substitutions and shall be included within the protection scope of the present invention.

Claims

1. A joint beamforming and deployment method for dual-intelligent reflector-assisted communication, applied to a wireless communication system with dual-intelligent reflector assistance, the wireless communication system comprising at least one access point with M antennas, and two access points with N antennas. I One passive reflector unit with an intelligent reflective surface, two intelligent reflective surface controllers, and one deployment area. and 1 target area Its features are, The joint beamforming and deployment method includes the following steps: S1, Input Deployment Area and target area Location information; S2. Calculate and configure the phase and transmission power of the access point's transmitted signal; S3. Construct and decompose the joint beamforming and deployment problem of intelligent reflectors; the process is as follows: S3.1, The problem of intelligent reflector joint beamforming and deployment is defined as follows: For the target area Position in the xy plane The signal-to-noise ratio is expressed as: in, Defined as an approximately negligible cross term. θ k Defined as the phase shift vector of the passive reflective unit of the k-th smart reflective surface, k∈{1,2}, r k Let P be the reference point of the k-th intelligent reflective surface in three-dimensional space. t The transmit power of the access point, The variance of additive white Gaussian noise, For the k-th intelligent reflective surface to the target area Position in the xy plane Far-field line-of-sight channel, Θ k Let G be the reflection phase shift matrix of the k-th smart reflector. k (r k ) represents the far-field line-of-sight channel from the access point to the k-th smart reflector, v * To assign the optimal transmission beamforming vector to the access point, Let n be the phase shift of the nth passive reflective element in the kth smart reflective surface. Let r be the position of the target region A in three-dimensional space. c For deployment area At the midpoint of the xy plane, For about φ T，k (r k ,d) and η T，k (r k d) Spatial frequency along the x-axis dimension, φ T，k (r k ,d) and η T，k (r k d) represent the distance from the k-th intelligent reflective surface to the target area. Position in the xy plane The launch elevation angle and launch azimuth angle, For about φ R，k (r k ) and η R，k (r k Spatial frequency along the x-axis dimension, φ R，k (r k ) and η R，k (r k ) represent the elevation angle and azimuth angle from the access point to the k-th intelligent reflector, respectively; Based on the above formula, two smart reflective surfaces are used to cover the two surfaces respectively. Two equally divided sub-target regions and Right now This simplifies the dual-smart reflector joint beamforming and deployment to a single-smart reflector joint beamforming and deployment; st is defined as constrained by max x f(x) is defined as maximizing the objective function f(x), min x f(x) is defined as minimizing the objective function f(x); therefore, the problem of joint beamforming and deployment of smart reflectors is expressed as: in, Corresponding access point to target sub-region Array gain at the receiving point Corresponding access point to target sub-region Multiplicative distance path loss at the receiving point, where c0 is the deployment area. The horizontal distance between the midpoint of the x-axis and the y-axis, R x For deployment area Length; S3.

2. The above-mentioned intelligent reflector joint beamforming and deployment problem is broken down into two sub-problems: 1) the intelligent reflector phase shift optimization problem and 2) the intelligent reflector deployment optimization problem, as follows: By decomposing the aforementioned smart reflector joint beamforming and deployment problem into two sub-problems: 1) the smart reflector phase shift optimization problem and 2) the smart reflector deployment optimization problem, a lower bound on the optimal solution of the aforementioned smart reflector joint beamforming and deployment problem is obtained; the first smart reflector phase shift optimization problem is expressed as: The second intelligent reflective surface deployment optimization problem is expressed as: in, Defined as the phase shift vector of the passive reflection unit of the intelligent reflector obtained after solving the above-mentioned intelligent reflector phase shift optimization problem; S4. For a given arbitrary smart reflector deployment, calculate the phase shift of the passive reflector unit of the smart reflector. S5. Based on the phase shift of the passive reflection unit of the intelligent reflective surface, calculate and deploy the intelligent reflective surface deployment position; S6. Based on the deployment location of the intelligent reflective surface, calculate and configure the phase shift of the passive reflective unit of the intelligent reflective surface.

2. The method for joint beamforming and deployment of dual-intelligent reflector-assisted communication according to claim 1, characterized in that, The process of step S1 is as follows: Enter the following information about the deployment region. and target area Location information: Assuming all location information is based on a three-dimensional Cartesian coordinate system with x, y, and z axes, and the height of each smart reflector is represented by H, the deployment area... The horizontal distance between the x-axis and the x-axis is represented by D>0, and the deployment area is... The midpoint of the xy plane is denoted as r. c =[c0, D] T The reference point of the k-th intelligent reflective surface in the xy plane is denoted as... The reference point of the k-th intelligent reflective surface in three-dimensional space is represented as: Where k∈{1,2}, and the superscript (·) T Defined as the transpose operation; target area The length is represented as D x Target area The width is represented as D y Target area The position in three-dimensional space is represented as target area The position in the xy plane is represented as d = [d x ,d y ] T ,in, 3. The method for joint beamforming and deployment of dual intelligent reflector-assisted communication according to claim 2, characterized in that, The process of step S2 is as follows: The one-dimensional steering vector function is defined as: Where ζ is defined as the phase difference between signals arriving or transmitted from two adjacent antennas or passive reflectors, and N t Defined as the size of a uniform linear array. The wavelength of the transmitted signal is denoted by λ, and the distance between two adjacent passive reflective elements is denoted by Ψ. I The number of passive reflective elements along the x-axis and z-axis of each smart reflective surface is represented by N. x and N z The elevation angle and azimuth angle of arrival from the access point to the k-th intelligent reflector are respectively denoted as φ. R，k (r k ) and η R，k (r k The receiving array response of the k-th smart reflector is expressed as: Where, k∈{1,2}, Indicates the Kronecker product. For about φ R，k (r k ) and η R，k (r k Spatial frequency along the x-axis dimension, For about η R,k (r k Spatial frequency along the z-axis dimension; Let ||||| be the space of a×b complex matrices, and ||·|| be the 2-norm operation, with the superscript (·). H Defined as the conjugate transpose operation. Defined as from the access point to the deployment area The transmission array response, ||a T (r c )|| 2 =M; The far-field line-of-sight channel from the access point to the k-th smart reflector is represented as: Wherein, β0 is defined as the channel gain at a reference distance of 1 meter. Defined as the distance from the access point to the k-th smart reflective surface; The response of the reflection array of the k-th smart reflective surface is expressed as: in, Defined as about φ T，k (r k ,d) and η T，k (r k d) Spatial frequency along the x-axis dimension Defined as about φ T，k (r k d) Spatial frequency along the z-axis; the k-th intelligent reflective surface to the target area Position in the xy plane The far-field line-of-sight channel is represented as: in, Defined as the k-th intelligent reflective surface to the target area Position in the xy plane The distance; diag(x) is defined as a diagonal matrix where each diagonal element is the corresponding element in x. The reflection phase shift matrix of the k-th intelligent reflector is expressed as: Defined as the phase shift vector of the passive reflective element of the k-th smart reflector; the transmission beamforming vector of the access point is expressed as... ||v|| = 1; Target region Position in the xy plane The received signal is represented as: Where x is the transmitted signal at the access point, and n0 is the signal with zero mean and variance. Additive white Gaussian noise; c * The superscript indicates the optimal value of variable c; in a given deployment area and target area Given the location information, according to the maximum ratio transmission theory, the optimal transmission beamforming vector of the access point is expressed as: According to the optimal transmission beamforming vector v * and the transmit power P of the access point t The beamforming controller at the access point sets the phase and transmit power of the transmitted signal.

4. The method for joint beamforming and deployment of dual intelligent reflector-assisted communication according to claim 3, characterized in that, The process of step S4 is as follows: S4.1 By dividing the k-th intelligent reflector into multiple sub-arrays, the coverage bandwidth of the k-th intelligent reflector is made greater than that of the corresponding target sub-region. The required waveform width is determined as follows: First, let N I The beam is divided into L equal-sized subarrays, with the beam pointing in a direction sufficient for space. Each subarray has N... s =N I / L reflective units; the spatial frequency direction pointed to by the sub-beams of the cluster of the l-th sub-array of the k-th smart reflective surface is represented as Where, φ k，l and η k，l Let be the elevation and azimuth angles of the l-th subarray of the k-th smart reflector, respectively; and let α be the common phase coefficient of the l-th subarray of the k-th smart reflector. k，l Each set of intelligent reflective surface subarrays is represented as Each set of intelligent reflective surface subarrays is represented as: The coverage bandwidth of the L subarrays of each smart reflector is represented by Ω. L (L), covering the target area The required angle range is expressed as in, Defined as the target area to be covered Minimum required angle Defined as the target area to be covered The maximum required angle; by dividing the k-th smart reflector into multiple sub-arrays, the coverage width of the k-th smart reflector is greater than that of the corresponding target sub-region. The required wavewidth is specifically expressed as: S4.2, Set the set of spatial frequency directions pointed to by the sub-beams of the cluster of the l-th subarray of the k-th smart reflector. The set of common phase coefficients of the k-th smart reflector and the l-th subarray. Make the array gain of the k-th smart reflector in the corresponding target region The inner approximate equality is determined as follows: Set spatial frequency interval The coverage wavelength for each subarray is defined by the spatial frequency resolution of the subarray. They are separated; therefore, the spatial frequency directions of the subarrays of the first and second smart reflectors are represented as follows: Where, Φ 1，1 and Φ 2，1 The starting spatial frequency directions of the first and second smart reflectors are defined respectively; the intersection point of adjacent subarrays of the k-th smart reflector is denoted as Ω. k，t Let t = 1, ..., L-1, and the intersection point between the first and second intelligent reflective surfaces be denoted as... To flatten the beam gain generated by the intersection points of all adjacent subarrays of the k-th smart reflector, the intersection point Ω of the adjacent subarrays of the k-th smart reflector... k，t The intersection points between t=1,...,L-1 and the first and second smart reflective surfaces. The phases at all points should be the same, specifically expressed as: According to the above formula, the common phase coefficient α of the l-th subarray of the k-th smart reflector is... k，l Set to: in, and S4.3 Setting the optimal number of subarrays L * (r k ) and the number of passive reflective elements in the subarray The process for solving the phase shift of the passive reflective element of the k-th smart reflective surface is as follows: First, according to the settings in steps S4.2 and S4.3, Therefore, the optimal number of subarrays and the optimal number of passive reflective elements in the subarrays are expressed as follows: The initial spatial frequency directions of the first and second smart reflective surfaces are respectively represented as: Based on the above L * (r k ),as well as The optimal spatial frequency direction and common phase coefficient of the intelligent reflector are expressed as follows: in, and Based on the above and The phase shift of the nth passive reflective element of the kth smart reflective surface is expressed as:

5. The method for joint beamforming and deployment of dual intelligent reflector-assisted communication according to claim 4, characterized in that, The process of step S5 is as follows: Based on the phase shift of the passive reflective unit of the smart reflective surface described in step S4, the worst-case array gain is expressed as: Combining the above equations, the aforementioned intelligent reflective surface deployment optimization problem can be rewritten as: The aforementioned optimization problem for the deployment of intelligent reflective surfaces can be further simplified to: Single-variable optimization problem: in, Then, based on the location of the intelligent reflective surface obtained by the one-dimensional search algorithm, the dual intelligent reflective surfaces are deployed in the deployment area.

6. The method for joint beamforming and deployment of dual intelligent reflector-assisted communication according to claim 1, characterized in that, The process of step S6 is as follows: Substituting the deployment location of the smart reflector described in step S5 into the following formula, we can obtain the phase shift of the nth passive reflective unit of the smart reflector: According to the above formula, each smart reflector controller sets the phase shift of the passive reflective unit of each smart reflector.

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