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一种智能反射面辅助的车辆通信网络传输优化方案

程诺 梁彦

移动通信2024,Vol.48Issue(9):16-23,8.
移动通信2024,Vol.48Issue(9):16-23,8.DOI:10.3969/j.issn.1006-1010.20230513-0001

一种智能反射面辅助的车辆通信网络传输优化方案

An Intelligent Reflecting Surface-Assisted Optimization Scheme for Vehicle Communication Networks

程诺 1梁彦1

作者信息

  • 1. 南京邮电大学通信与信息工程学院,江苏 南京 210003
  • 折叠

摘要

Abstract

Vehicle communication network technology can enable efficient communication and information exchange between vehicles and infrastructure,thereby improving road safety,traffic efficiency,and user experience.Given the complex propagation environment in modern cities,especially the hindrance of urban buildings and the influence of vehicle high-speed movement,the vehicle communication link is prone to degradation,resulting in impaired performance of the vehicle communication network.To obtain more reliable communication links,intelligent reflecting surfaces(IRS)have become an effective auxiliary method for vehicle communication networks.In this paper,for the vehicle-to-infrastructure communication scenario,the multi-user sum-rate optimization problem of the IRS-assisted vehicle communication network is investigated,subject to the constraint on IRS reflection coefficient and base station transmitting power.Aiming at the problem that it is difficult for the base station to obtain perfect instantaneous channel state information(CSI),an IRS-assisted optimization scheme for vehicle communication networks based on statistical CSI is designed.The optimization objective is modeled as the sum rate of multiple users.To solve the accurate acquisition of instantaneous CSI during vehicle rapid motion,a statistical CSI-based system optimization model is established.However,this optimization problem is a non-convex NP-hard problem that is difficult to solve directly.Therefore,a fractional programming method is adopted to handle the objective function.The problem is transformed into manageable subproblems by introducing two auxiliary variables.Once manageable subproblems are obtained,their mathematical expectations are calculated.Finally,an iteration algorithm based on block coordinate descent is employed to achieve joint optimization of base station beamforming and IRS passive beamforming.On the one hand,the Lagrange dual method is used to optimize the base station beamforming matrix and obtain the optimal solution.On the other hand,the sequential convex approximation method is adopted to solve the passive beamforming problem of IRS.According to the idea of the block coordinate descent algorithm,during the optimization of the base station beamforming matrix,the IRS passive beamforming is set to a fixed value,and during the optimization of the intelligent passive beamforming phase,the base station beamforming is set to a fixed value.The proposed optimization scheme is compared with two schemes:Scheme 1 is the beamforming matrix optimization scheme and the IRS random phase scheme,and Scheme 2 is the maximum ratio transmission beamforming scheme for the base station and the IRS random phase scheme.Simulation results show that compared with the benchmark schemes,the proposed scheme significantly improves the sum rate of the vehicle communication network.

关键词

智能反射面/车辆通信/统计信道状态信息/优化传输方案

Key words

intelligent reflecting surface/vehicle communication/statistical channel state information/transmission optimization scheme

分类

电子信息工程

引用本文复制引用

程诺,梁彦..一种智能反射面辅助的车辆通信网络传输优化方案[J].移动通信,2024,48(9):16-23,8.

基金项目

国家自然科学基金"大规模3D MIMO系统基于量子神经网络的信道建模及其稀疏估计方法研究"(61871238) (61871238)

移动通信

1006-1010

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