CN-122001409-A - RIS phase shift optimization and beam forming method and system based on computable channels

CN122001409ACN 122001409 ACN122001409 ACN 122001409ACN-122001409-A

Abstract

The invention relates to a RIS phase shift optimization and beam forming method and system based on a computable channel, which are used for calculating channels from a base station to the RIS and from the RIS to a user based on the positions of the base station, the RIS and the user, establishing an optimization problem by utilizing a maximum channel capacity criterion, restraining the channels by combining the positions, optimizing a phase shift matrix of a RIS reflecting unit by adopting a Riemann manifold optimization algorithm and a Riemann conjugate gradient algorithm, carrying out optimal RIS reflecting path adjustment, and obtaining a full-digital beam forming matrix by utilizing the adjusted RIS reflecting path by the base station and the user, designing a mixed beam forming matrix and optimizing the frequency spectrum efficiency. In the invention, the base station calculates the azimuth angle and the path gain of the transmitting beam according to the RIS and the user position, and after feedback, the intelligent reflecting surface adjusts the reflecting angle according to the feedback angle information, and meanwhile, the base station end and the user end are designed with mixed beam forming, thereby effectively improving the frequency spectrum efficiency of the system and solving the millimeter wave transmission bottleneck.

Inventors

WANG PENG
WANG XI
WEN LU
CHEN LIYUN
TIAN BING
PENG XIANCHEN
CHEN ZHIYING
CHEN XINLONG
ZHANG NA
CAI HAIYAN

Assignees

中铁第一勘察设计院集团有限公司

Dates

Publication Date: 20260508
Application Date: 20260410

Claims (10)

1. The RIS phase shift optimization and beam forming method based on the computable channel is characterized in that: The method comprises the following steps: S1, calculating channels from a base station to an RIS and from the RIS to a user based on the positions of the base station, the RIS and the user; S2, establishing an optimization problem by utilizing a maximum channel capacity criterion, and restricting a channel by combining the positions; s3, optimizing a phase shift matrix of the RIS reflection unit by adopting a Riemann manifold optimization algorithm and a Riemann conjugate gradient algorithm, and carrying out optimal RIS reflection path adjustment; And S4, the base station and the user acquire an all-digital beam forming matrix by utilizing the adjusted RIS reflection path, and design a mixed beam forming matrix to optimize the frequency spectrum efficiency.
2. The method for optimizing and beamforming RIS phase shift based on computable channels as claimed in claim 1, wherein: based on the locations of the base station, the RIS and the user, base station to RIS and RIS to user channels are calculated, Comprising the following steps: s101, calculating azimuth angles according to the positions of the base station, the RIS and the user: Wherein: Is the centroid position of the user; is the location of the RIS; is the location of the base station; a scatterer location for the base station to the RIS; a scatterer location for the RIS to the user; 、 For horizontal and vertical incidence angles at the RIS end, For the horizontal angle of incidence of the p-th non-straight diameter, For normal incidence of the p-th non-straight diameter, For the DOA at the BS side, Is DOA of the BS end of the p-th non-straight diameter, For the DOA at the UE side, For the DOA at the UE end of the first non-straight-line path, 、 The horizontal reflection angle and the vertical reflection angle of the RIS end are respectively, A horizontal reflection angle for the first non-straight diameter; a vertical reflection angle which is the first non-straight diameter; s102, calculating a path gain, wherein the path gain obeys : ; Wherein: Is the total path loss; a is the reference path loss; b is the path loss index; is the distance between the receiving and transmitting ends; is shadow fading; s103, acquiring array response vectors: The base station and the user employ an array response vector of a uniform linear array: ; Wherein: is an array response vector; for the normalization factor, the power of the vector is ensured to be 1, ; Is the signal wavelength; The included angle between the signal incidence direction and the array normal is set; the distance between adjacent antennas at the base station end is the distance; RIS employs an array response vector for a uniform planar array: ; Wherein: for the array response vector of the RIS, Respectively a horizontal angle and a vertical angle; For the number of RIS reflection units, , ; Then all array response matrices are: Wherein: a transmitting array response matrix of the base station end; a receiving array response matrix of the RIS terminal; a diagonal matrix for the path gain from the base station to the RIS; M is the number of base station antennas and RIS reflecting units respectively; Is a large-scale path loss; The reflection array response matrix is the RIS end; a receiving array response matrix for the user terminal; a diagonal matrix for the path gain of the RIS to the user; s104, calculating a channel from the base station to the RIS and from the RIS to the user: Base station to RIS channel matrix The method comprises the following steps: ; Wherein: transmitting the conjugate transpose of the array response matrix for the base station end; RIS to user channel matrix The method comprises the following steps: ; Wherein: the method comprises the steps of (1) transpose the conjugate of a RIS end reflection array response matrix; Base station to RIS, and RIS to user channels Expressed as: ; Wherein: representing a phase shift matrix of the intelligent reflective surface; ; ; Wherein: equivalent scalar gain after RIS reflection for the first path; And A transmit vector and a receive vector of the RIS, respectively; Representing a concatenated array response vector.
3. The method for optimizing and beamforming RIS phase shift based on computable channels as claimed in claim 2, wherein: the base station obtains the user position through the positioning technology, shares the real-time position, and the RIS is controlled by the base station through the controller.
4. A method of rim phase shift optimization and beamforming based on computable channels as claimed in claim 3, wherein: establishing an optimization problem using maximum channel capacity criteria and constraining the channel in conjunction with location, including: s201, establishing optimization problem by maximum channel capacity criterion : Wherein: ; ; And Respectively retained by the original matrix A representative set of column vectors is composed of, And Then by the corresponding The effective diagonal terms are formed; S202, restraining channels by combining positions, obtaining LOS path array response vectors as a first column of an array response matrix, and the other columns The column array response vector is obtained through the minimum azimuth angle error, and the selected RIS arrival angle index is obtained Is set of (a) The method comprises the following steps: ; The selected RIS departure angle index Aggregation The method comprises the following steps: 。
5. the method for optimizing and beamforming RIS phase shift based on computable channels as claimed in claim 4, wherein: Optimizing the phase shift matrix of the RIS reflection unit by adopting a Riemann manifold optimization algorithm and a Riemann conjugate gradient algorithm, comprising: S301, obtaining corresponding 、、、 , The optimization problem of (a) is modified into : S302, solving by using Riemann conjugate gradient algorithm The phase shift matrix of the RIS reflection unit is optimized.
6. The method for optimizing and beamforming RIS phase shift based on computable channels as claimed in claim 5, wherein: Solving by using Riemann conjugate gradient algorithm Optimizing a phase shift matrix of an RIS reflection unit, comprising: calculating Riemann gradient: wherein the Euclidean gradient of the objective function is: Wherein: A RIS phase shift matrix to be optimized; a response vector matrix for the cascade array; is an equivalent signal-to-noise factor; In the searching direction, a line searching algorithm based on a Riemann conjugate gradient algorithm is adopted, and a step length updating rule is as follows: Wherein: To update the Riemann gradient; updating parameters for Polak-Ribiere; Is defined as Performing a retract, the retract operator being defined to find the next point by mapping it to tangent space The update scheme is in the form of: Wherein: is Armijo step length; for the updated RIS phase shift matrix, For the RIS phase shift matrix before updating.
7. The method for optimizing and beamforming RIS phase shift based on computable channels as claimed in claim 6, wherein: The base station and the user acquire an all-digital beam forming matrix by utilizing the adjusted RIS reflection path, and design a mixed beam forming matrix to optimize the frequency spectrum efficiency, comprising: S401, under the joint constraint condition of the analog domain and the digital domain, the spectrum efficiency optimization problem is expressed as : S402, will be Decomposing into base station end mixed wave beam forming matrix And (3) with And a user mixed beam forming matrix And (3) with Two sub-problems; in order to simulate the precoding matrix, In order to simulate the combination matrix, A matrix of the digital pre-code is provided, A digital combining matrix; S403, the analog beamforming matrix of the fully connected structure is expressed as: Wherein: And Respectively corresponding emission angles Angle of reception with A corresponding beamforming vector; s404, optimizing problem from original Removing variable and constraint items of digital domain, and simplifying the variable and constraint items into analog domain beam forming to maximize spectrum efficiency : S405, loosening the joint optimization by decoupling the optimization variables and updating the joint optimization in stages; s406, optimizing the digital domain beamforming matrix based on MMSE criterion And 。
8. The method for optimizing and beamforming RIS phase shift based on computable channels as claimed in claim 7, wherein: relaxing the joint optimization by decoupling the optimization variables and updating it in stages, comprising: In the first phase, a given update is made A kind of electronic device In the second phase, the given update is performed A kind of electronic device Problems are derived And : 。
9. The method for optimizing and beamforming RIS phase shift based on computable channels as claimed in claim 8, wherein: Optimizing digital domain beamforming matrix based on MMSE criterion And Comprising: Formally representing the digital beamforming matrix optimization problem as: Except for The constraint is such that, Without other constraints, the priority determination is as follows according to the MMSE criterion: ; Wherein: ; The result of the signal estimation is expressed as: ; And The MMSE problem between is expressed as: ; The problem is equivalent to: ; Based on orthogonality of data streams and equivalent channel matrix Digital beam forming matrix based on MMSE criterion calculation 、。
10. RIS phase shift optimization and beam forming system based on computable channels, characterized in that: The system for implementing the method of any one of claims 1-9, comprising: the channel calculation module is used for calculating channels from the base station to the RIS and from the RIS to the user based on the positions of the base station, the RIS and the user; The optimization problem establishing module is used for establishing an optimization problem by utilizing the maximum channel capacity criterion and restraining the channel by combining the positions; the phase shift matrix optimization module is used for optimizing a phase shift matrix of the RIS reflection unit by adopting a Riemann manifold optimization algorithm and a Riemann conjugate gradient algorithm, and carrying out optimal RIS reflection path adjustment; and the beam forming design module is used for acquiring an all-digital beam forming matrix by the base station and the user through the adjusted RIS reflection path, designing a mixed beam forming matrix and optimizing the frequency spectrum efficiency.

Description

RIS phase shift optimization and beam forming method and system based on computable channels Technical Field The invention relates to the technical field of wireless communication, in particular to a RIS phase shift optimization and beam forming method and system based on a computable channel. Background The generation-to-generation evolution of the wireless communication technology is driving society to change to intelligent acceleration, the 1G to 4G times focus on the improvement of transmission rate and communication quality, and the 5G times realize the emerging applications of high bandwidth, low time delay, high reliability, internet of things support, automatic driving and the like. The current global communication industry has entered the 6G research and development stage to break through the 5G performance boundary and build a new paradigm of environmental intelligence. Millimeter wave communication has become a key technical direction by virtue of Tbps (terabit per second) level transmission potential, but its practical deployment faces three major challenges, namely high-band signal attenuation and path loss, weak penetration capability, and high complexity of a massive MIMO (Multiple-Input Multiple-Output) antenna system. In order to solve the above challenges, the industry adopts hybrid beamforming technology to balance performance and energy consumption, and realizes cost optimization through radio frequency chain reduction. Notably, the smart reflective surface (also referred to as reconfigurable smart surface, reconfigurable Intelligent Surface, RIS) technology presents the unique advantage that by dynamically regulating electromagnetic propagation paths, the smart reflective surface not only can enhance millimeter wave coverage, alleviate shielding effects, but also has the sustainable characteristics of low power consumption and easy deployment. The 6G network in the future is expected to realize the coordination of communication and sensing, namely the integration of communication and sensing, and the cooperative architecture can combine the communication network with an environment sensing system to realize the capabilities of information interaction, real-time sensing, analysis and response to environment change. The perception position information is taken as an important component in the perception environment information, and good research results are obtained at present. Along with the development of 6G sense-of-general integration trend, the fusion of high-precision positioning technology and edge calculation provides a new paradigm for real-time channel parameter estimation and beam optimization. The environment sensing capability can promote the communication system to develop to a self-adaption and intelligent direction, so that the frequency spectrum efficiency is effectively improved, and the operation cost is reduced. However, in the case that an intelligent reflection surface is configured in a millimeter wave massive MIMO point-to-point downlink communication system and a direct link between a User Equipment (UE) and a Base Station (BS) is blocked, how to maximize the spectrum efficiency of the communication system is still lacking in determining an effective method, and therefore, it is necessary to propose new measures to overcome this drawback. Disclosure of Invention The invention aims to provide an RIS phase shift optimization and beam forming method and system based on a computable channel, which are used for solving the problem that a method for maximizing the frequency spectrum efficiency of a communication system is lacking at present. In order to achieve the above purpose, the technical scheme adopted by the invention is as follows: providing a method of RIS phase shift optimization and beamforming based on a computable channel, the method comprising: S1, calculating channels from a base station to an RIS and from the RIS to a user based on the positions of the base station, the RIS and the user; S2, establishing an optimization problem by utilizing a maximum channel capacity criterion, and restricting a channel by combining the positions; s3, optimizing a phase shift matrix of the RIS reflection unit by adopting a Riemann manifold optimization algorithm and a Riemann conjugate gradient algorithm, and carrying out optimal RIS reflection path adjustment; And S4, the base station and the user acquire an all-digital beam forming matrix by utilizing the adjusted RIS reflection path, and design a mixed beam forming matrix to optimize the frequency spectrum efficiency. Further, calculating base station to RIS and RIS to user channels based on the locations of the base station, RIS and user, comprises: s101, calculating azimuth angles according to the positions of the base station, the RIS and the user: Wherein: Is the centroid position of the user; is the location of the RIS; is the location of the base station; a scatterer location for the base station to the RIS; a s