单天线功率约束和统计CSI下的MU-MIMO下行链路线性预编码  

Linear Precoding for MU-MIMO Downlink with Per-Antenna Antenna Power Constraint and Statistical CSI

作　　者：张国洋 戴旭初[1] ZHANG Guoyang;DAI Xuchu(University of Science and Technology of China,Hefei Anhui 230026,China)

机构地区：[1]中国科学技术大学,安徽合肥230026

出　　处：《通信技术》2023年第11期1233-1241,共9页Communications Technology

摘　　要：近年来,多用户多输入多输出(Multiple-User Multiple-Input Multiple-Output,MU-MIMO)下行链路的预编码算法设计吸引了越来越多研究者的兴趣。然而目前并没有对基站端已知信道误差概率分布且约束条件为单天线功率约束(Per-Antenna Power Constraints,PAPCS)的情况下的线性预编码算法的研究。针对上述情况,以遍历和速率(Expected Sum Rate)最大化为优化准则,主要基于约束随机逐次凸近似(Constrained Stochastic Successive Convex Approximation,CSSCA)、二阶对偶法、交替方向乘子法(Alternating Direction Method of Multipliers,ADMM)及高斯随机化(Gaussian Randomization)设计了线性预编码算法。所提算法的适用场景更符合实际情况,而且实验仿真结果证明,算法的性能较好。In recent years,the design of linear precoding algorithms for MU-MIMO(Multi-User Multiple-Input Multiple-Output)downlink systems attracts increasing interest from researchers.However,currently there is no research on linear precoding algorithms under the constraint of PAPCS(Per-Antenna Power Constraints)with known channel error probability distribution at the base station.To address this issue,linear precoding algorithms based on different optimization criteria are proposed,considering the objectives of traversal and maximum expected sum rate.Some of these algorithms are designed based on CSSCA(Constrained Stochastic Successive Convex Approximation),second-order duality,ADMM(Alternating Direction Method of Multipliers),and Gaussian randomization techniques.These algorithms are more suitable for practical applications and perform well through experimental simulations.

关 键 词：多用户MIMO 遍历和速率 约束随机逐次凸近似 交替方向乘子法 高斯随机化 

分 类 号：TN971[电子电信—信号与信息处理]