Decentralized Recursive MMSE Equalizer for Massive MIMO Systems

Abstract

In massive multiple-input multiple-output (MIMO) systems, linear equalizers such as zero-forcing (ZF) and minimum mean-square error (MMSE) equalizers are often used and implemented in a centralized way. As the antenna number increases, the centralized equalization requires a huge data exchange rate as well as intensive central processing capability. Decentralized equalization can alleviate this bottleneck by partitioning the antenna array into multiple clusters and conducting equalization separately and locally. In this paper, we design a decentralized MMSE equalizer based on the chain architecture. The proposed equalizer is conducted in a recursive manner through a chain and generates a sequence of estimated signals that converge to the MMSE solution. Furthermore, we also propose an early termination strategy according to channel quality, thus reducing complexity and data exchange rate. Simulation results illustrate that the proposed recursive MMSE equalizer outperforms the existing decentralized equalizer, and achieves the same BER performance as the centralized MMSE equalizer with a lower data exchange rate.