基于硬件损伤与离散相移的IRS辅助MU-MISO通信系统鲁棒能效优化算法  

Robust Energy-Efficient Optimization Algorithm for Intelligent Reflecting Surface-Aided MU-MISO Communication Systems with Hardware Impairments and Discrete Phases

作　　者：熊迎香 徐勇军[1] 陈前斌[1] 黄崇文 XIONG Ying-xiang;XU Yong-jun;CHEN Qian-bin;HUANG Chong-wen(School of Communications and Information Engineering,Chongqing University of Posts and Telecommunications,Chongqing 400065,China;College of Information Science&Electronic Engineering,Zhejiang University,Hangzhou,Zhejiang 310027,China)

机构地区：[1]重庆邮电大学通信与信息工程学院,重庆400065 [2]浙江大学信息与电子工程学院,浙江杭州310027

出　　处：《电子学报》2024年第6期1832-1841,共10页Acta Electronica Sinica

基　　金：国家自然科学基金(No.U23A20279,No.62271094);重庆市自然科学基金(No.CSTB2022NSCQLZX0009,No.CSTB2022NSCQ-LZX0025);重庆市教委科学技术研究(No.KJZD-K202200601)。

摘　　要：针对现有工作仅考虑理想信道状态信息(Channel State Information,CSI)与硬件调控能力导致在实际系统中用户传输中断过高的问题,该文综合考虑不完美CSI、有限相移调控、硬件损伤的影响,提出了一种基于智能反射面(Intelligent Reflecting Surface,IRS)辅助的鲁棒能效优化算法.考虑基站最大发射功率与IRS离散相移约束及差异化用户传输速率需求,基于高斯CSI误差模型和加性硬件损伤模型,将基站主动波束成形与IRS被动相移优化问题建模为含不确定性参数的多变量耦合能效最大化问题.考虑波束向量与相移矩阵的耦合性,利用交替优化策略将原问题转化为主动波束子问题和离散相移子问题.利用伯恩斯坦不等式、丁克尔巴赫方法及连续凸近似将波束子问题转化为凸优化问题求解;基于求解的主动波束向量,利用罚函数法和投影定理求解离散相移子问题.仿真结果表明,与传统非鲁棒算法相比,所提算法能效性能提升15.8%,平均中断概率间隙达86.7%.Aiming at the problem that most of the existing works only consider the ideal channel state information(CSI)and hardware regulation capability,leading to high user transmission outages in real systems,considering the impact of imperfect CSI,limited phase-shift modulation and hardware impairments(HWIs),a robust energy-efficient(EE)optimization algorithm with the help of intelligent reflecting surface(IRS)was proposed in this paper.Taking the constraints of the maximum transmit power of the base station(BS),the discrete phase of the IRS,and the diverse transmission rate requirements of users into account,a joint optimization problem of the active beamforming of the BS and the passive beamforming of the IRS based on Gaussian CSI error models and additive HWI models was formulated as a multivariate and coupled energy-efficient maximization problem with uncertain parameters.Considering the coupled relationship between beamforming vectors and phase-shift matrices,the original problem was transformed into an active beamforming subproblem and a discrete phase-shift subproblem via an alternating optimization strategy.The former was converted into a convex problem by using Bernstein’s inequality,Dinkelbach’s method,and successive convex approximation.Then,the discrete phase-shift subproblem with the solved active beamforming vectors was resolved by applying the penalty function method and the projection theorem.Simulation results showed that the EE was improved by 15.8%and the outage gap reached 86.7%,compared to the traditional non-robust algorithm.

关 键 词：智能反射面 能效优化 鲁棒性 

分 类 号：TN929.5[电子电信—通信与信息系统]