CN-121984541-A - Phase shift optimization method and system for communication perception network

CN121984541ACN 121984541 ACN121984541 ACN 121984541ACN-121984541-A

Abstract

The embodiment of the application provides a phase shift optimization method and a phase shift optimization system for a communication awareness network, which can solve the technical problem of poor overall performance of a wireless system in the related art. The method comprises the steps of determining signal interference-to-noise ratio and beam pattern gain of each user in a clustering result based on a phase shift vector of a super surface, constructing a phase shift optimization function based on the signal interference-to-noise ratio, the beam pattern gain and amplitude constraint of the super surface, and obtaining the phase shift optimization result under the condition that the phase shift optimization function meets convergence conditions. The limitation of coverage is overcome, and higher freedom degree is obtained by dynamically adjusting the transmission and reflection factors of the units. And adopting a penalty function method, taking the rank one constraint as a penalty term, and solving the local optimal solution of the original problem by continuously improving the penalty factor iteration. The maximization of the beam pattern gain in the minimum perception target direction is realized under the condition of meeting the service quality of the communication user, the perception performance is improved, high delay and communication failure are prevented, and the reliability and the stability of the system are improved.

Inventors

WANG TIANQI
DONG JIANGBO
ZHANG DONGCHEN
XING FENG

Assignees

中国移动通信集团设计院有限公司
中国移动通信集团有限公司

Dates

Publication Date: 20260505
Application Date: 20251217

Claims (10)

1. A phase shift optimization method for a communication aware network, the method comprising: determining the signal interference-to-noise ratio and the beam pattern gain of each user in the clustering result based on the phase shift vector of the super surface; constructing a phase shift optimization function based on the signal-to-interference-and-noise ratio, the beam pattern gain and the amplitude constraint of the super surface; and under the condition that the phase shift optimization function meets the convergence condition, obtaining a phase shift optimization result.
2. The phase shift optimization method for a communication aware network according to claim 1, wherein determining signal to interference-plus-noise ratios of individual users in the clustering result based on the super-surface phase shift vector comprises: distributing a beam to each clustering result, and determining the receiving signals of each user in the clustering result in the beam; And based on the received signals of all the users in the clustering result, performing serial interference elimination operation on the clustering result, and determining the signal interference to noise ratio of all the users in the clustering result.
3. The method of phase shift optimization for a communication aware network according to claim 2, wherein the clustering result comprises a first user and a second user, wherein the first user is closer to a super-surface than the second user is to the super-surface, wherein determining the signal-to-interference-and-noise ratio of each user in the clustering result based on the super-surface phase shift vector comprises: Obtaining a signal to interference-plus-noise ratio of the first user based on the power distribution factor of the first user, the out-of-cluster interference of the first user, the channel gain and the phase shift vector; obtaining a signal to interference and noise ratio of the second user relative to the first user based on the power distribution factor of the first user, the power distribution factor of the second user, the out-of-cluster interference of the first user, the channel gain and the phase shift vector; And obtaining the signal interference-to-noise ratio of the second user based on the power distribution factor of the first user, the power distribution factor of the second user, the out-of-cluster interference of the second user, the channel gain and the phase shift vector.
4. The phase shift optimization method for a communication aware network according to claim 1, wherein determining a beam pattern gain based on the phase shift vector of the super surface comprises: And determining the beam pattern gain based on the phase shift vector, the beam parameter, the channel gain and the target steering vector, wherein the target steering vector is used for representing the directional response of the array antenna transmitting signals, and the beam parameter is the parameter of the beam corresponding to the clustering result.
5. The method of phase shift optimization for a communication awareness network of claim 4 wherein said constructing a phase shift optimization function based on said signal-to-interference-and-noise ratio, said beam pattern gain, and said super-surface magnitude constraint comprises: introducing a semi-positive definite matrix and a penalty term into the phase shift optimization function to obtain an updated phase shift optimization function; and performing Taylor expansion on the updated phase shift optimization function to obtain a target optimization function.
6. The method according to claim 5, wherein the optimization objective of the objective optimization function includes maximizing a minimum value among perceptual performance indexes corresponding to each objective direction, and wherein the objective directions are determined based on the signal-to-interference-and-noise ratio, the beam pattern gain, and the magnitude constraint of the super surface, respectively.
7. The phase shift optimization method for a communication aware network according to claim 6, wherein the obtaining the phase shift optimization result in the case that the phase shift optimization function satisfies a convergence condition comprises: iteratively solving the target optimization function based on the phase shift angle; after each round of iteration is completed, the numerical value of the punishment item is adjusted so as to enable the target optimization function to converge; In the first place Optimal value after the iteration and at the first And under the condition that the optimal value of the secondary iteration is reduced to be smaller than or equal to a difference threshold value, judging that a convergence condition is met, and obtaining the phase shift optimization result, wherein t is a positive integer which is larger than or equal to 2.
8. The phase shift optimization method for a communication aware network according to any of claims 1-7, wherein determining the phase shift vector of the subsurface comprises: The phase shift vector is determined based on a phase shift angle and a first factor, the first factor being a transmission or reflection factor of the subsurface.
9. The phase shift optimization method for a communication aware network according to any of claims 1-7, wherein the supersurface is a simultaneous transflector reconfigurable intelligent surface STAR RIS.
10. A phase shift optimization system for a communication aware network, adapted to perform the method of any of claims 1 to 9.

Description

Phase shift optimization method and system for communication perception network Technical Field The embodiment of the application relates to the technical field of communication, in particular to a phase shift optimization method and a phase shift optimization system for a communication perception network. Background In a reconfigurable smart surface (Reconfigurable Intelligent Surface, RIS) phase shift design, a base station is connected to the RIS through a controller. The RIS itself is composed of a large number of programmable electromagnetic units, the phase shift parameters of which cannot be directly regulated and controlled by the base station, and the RIS itself must rely on a controller to transmit control instructions, so as to realize the dynamic configuration of the phases of the electromagnetic units. The controller can be a Field Programmable gate array (Field-Programmable GATE ARRAY, FPGA), the FPGA has high parallel processing capability and real-time response characteristic, synchronous updating of phase shift parameters of all units of the RIS can be completed in millisecond level or microsecond level, dynamic reconstruction of hardware logic is supported, phase shift adjustment requirements under different scenes can be adapted, and phase shift is dynamically adjusted to improve system performance. Compared with a single RIS which can only reflect signals from a base station, the coverage of a wireless network is limited, and the service coverage limitation of the RIS can be solved by adopting two RISs which are respectively responsible for reflection and transmission. However, since the two RIS are independent of each other, the resources and interference of the transmitting and reflecting areas cannot be more effectively coordinated by the RIS unit phase shift, limiting the overall performance of the wireless system. Disclosure of Invention The embodiment of the application provides a phase shift optimization method and a phase shift optimization system for a communication awareness network, which can solve the technical problem of poor overall performance of a wireless system in the related art. In a first aspect, an embodiment of the present application provides a phase shift optimization method for a communication perception network, where the method includes determining signal interference to noise ratio and beam pattern gain of each user in a clustering result based on a phase shift vector of a super surface, constructing a phase shift optimization function based on the signal interference to noise ratio, the beam pattern gain and an amplitude constraint of the super surface, and obtaining a phase shift optimization result when the phase shift optimization function meets a convergence condition. In one implementation manner of the first aspect, determining the signal-to-interference-and-noise ratio of each user in the clustering result based on the phase shift vector of the super surface includes allocating a beam to each clustering result, determining a received signal of each user in the clustering result at the beam, performing a serial interference cancellation operation on the clustering result based on the received signal of each user in the clustering result, and determining the signal-to-interference-and-noise ratio of each user in the clustering result. In one implementation manner of the first aspect, the clustering result comprises a first user and a second user, the distance between the first user and the super surface is closer than the distance between the second user and the super surface, determining the signal interference-to-noise ratio of each user in the clustering result based on the phase shift vector of the super surface comprises obtaining the signal interference-to-noise ratio of the first user based on the power distribution factor of the first user, the out-of-cluster interference of the first user, the channel gain and the phase shift vector, obtaining the signal interference-to-noise ratio of the second user relative to the first user based on the power distribution factor of the first user, the power distribution factor of the second user, the out-of-cluster interference of the second user, the channel gain and the phase shift vector, and obtaining the signal interference-to-noise ratio of the second user. In one implementation manner of the first aspect, the determining the beam pattern gain based on the phase shift vector of the super surface includes determining the beam pattern gain based on the phase shift vector, a beam parameter, a channel gain and a target steering vector, wherein the target steering vector is used for representing a directional response of a signal transmitted by the array antenna, and the beam parameter is a parameter of a beam corresponding to the clustering result. In one implementation manner of the first aspect, the phase shift optimization function is constructed based on signal interference to noise ratio, beam pattern