Decentralized Signal Detection via Expectation Propagation Algorithm for Uplink Massive MIMO Systems

Abstract

The existing centralized antenna array architecture and the corresponding centralized baseband processing based signal detection algorithms incur huge burden on the raw baseband data rates and chip input/output bandwidth for massive multiple-input multiple-output (MIMO) systems. In this paper, we propose a novel decentralized baseband processing based signal detection under the framework of the expectation propagation algorithm (EPA) for uplink massive MIMO systems. This architecture partitions the base station antennas into multiple independent antenna clusters, each associated with analog and digital modulation circuitry, independent radio-frequency chains, and computing hardwares. The antenna clusters only access local channel state information and require low communication bandwidth. In the proposed scheme, the decentralized processing unit executes local channel estimation and signal detection, and delivers the partial message to the centralized processing unit parallelly, where the message contains the local means and variances iteratively updated by the EPA detector from each antenna cluster. The centralized processing unit operates the message fusion based on the proposed message fusion rule for decoding operation. Simulation results illustrate that the proposed decentralized EPA signal detection approaches the conventional centralized one with marginal computational complexity overhead when the number of antenna clusters is small, and outperforms the state-of-the-art decentralized counterparts.