Approximate Expectation Propagation Massive MIMO Detector With Weighted Neumann-Series

Abstract

Expectation propagation (EP) achieves near-optimal performance for massive multiple-input multiple-output (MIMO) detection, however, at the cost of multiple expensive matrix inversions. An EP with approximation (EPA) algorithm has been introduced to address this issue, which maintains the good performance with only one matrix inversion for initialization. Nevertheless, the accuracy of this inversion has a strong impact on the convergence of EPA, which hinders the practical implementation of the algorithm. In this brief, a weighted Neumann series approximation (wNSA) is first proposed for explicit inverse matrix approximation, which attains enhanced convergence rate and accuracy compared to standard NSA for various MIMO antenna configurations. wNSA is then combined with EPA to propose an efficient, flexible, and hardware-friendly EPA-wNSA detector. Simulation results are illustrated to confirm the similar good performance of the proposed EPA-wNSA as EP. The hardware architecture of EPA-wNSA detector is also proposed and implemented on 65 nm CMOS technology. Implementation results show that this architecture achieves a throughput of 0.86 Gb/s, which outperforms state-of-the-art (SOA) EP-based detectors.