Communication-efficient distributed precoding design for Massive MIMO

Abstract

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

Keywords

• distributed precoding;data compression;deep learning;joint optimization