Massive MIMO中通信高效的分布式预编码设计  

Communication-efficient distributed precoding design for Massive MIMO

作　　者：李勉 李洋 张纵辉 史清江 LI Mian;LI Yang;ZHANG Zonghui;SHI Qingjiang(School of Science and Engineering,The Chinese University of Hong Kong(Shenzhen),Shenzhen 518172,China;Shenzhen Research Institute of Big Data,Shenzhen 518172,China;Pengcheng Laboratory,Shenzhen 518055,China;Pazhou Laboratory(Huangpu),Guangzhou 510555,China;School of Software Engineering,Tongji University,Shanghai 200092,China)

机构地区：[1]香港中文大学(深圳)理工学院,广东深圳518172 [2]深圳市大数据研究院,广东深圳518172 [3]鹏城国家实验室,广东深圳518055 [4]琶洲实验室(黄埔),广东广州510555 [5]同济大学软件学院,上海200092

出　　处：《通信学报》2023年第8期37-48,共12页Journal on Communications

基　　金：国家重点研发计划基金资助项目(No.2022YFA1003900);国家自然科学基金资助项目(No.62071409,No.62231019,No.62101349);深圳市科技基金资助项目(No.RCJC20210609104448114);鹏城实验室重点基金资助项目(No.PCL2023AS1-2)。

摘　　要：针对多BBU基带处理架构,提出一种通信高效的分布式预编码方案,旨在降低BBU间前传交互和计算复杂度。首先,提出基于R-WMMSE算法的分布式框架,利用最优解的子空间特性无损压缩交互数据,降低数据交互量。然后设计了2种基于矩阵乘法的可学习压缩模块,通过优化的计算结构和矩阵参数减少参数和计算量,并保持函数表达能力。最后,以可达速率为优化目标,将可学习模块和分布式预编码算法框架联合优化得到最终模型。所提方案可以在更低的数据交互和计算复杂度要求下,实现预编码性能的保障。A communication-efficient distributed precoding scheme was proposed for multi-baseband processing unit(BBU)baseband processing architecture,aiming to reduce fronthaul data exchange and computational complexity between BBUs.Firstly,a distributed framework based on R-WMMSE algorithm was proposed,which utilized the subspace property of the optimal solution to compress the interactive data losslessly,thereby reducing data exchange.Furthermore,two learnable compression modules based on matrix multiplication were designed,using optimized computing structures and matrix parameters to reduce the parameters and computations while maintaining function expressiveness.Finally,the learnable modules and the distributed precoding framework were jointly optimized with achievable rate as the optimization objective to obtain the final model.The proposed scheme can achieve guaranteed precoding performance under lower requirements on data interaction and computational complexity.

关 键 词：分布式预编码 数据压缩 深度学习 联合优化 

分 类 号：TN929.53[电子电信—通信与信息系统]