BiSPARCs for Unsourced Random Access in Massive MIMO

TL;DR

This paper introduces a novel coding scheme combining channel estimation, SPARC, and LDPC codes with a BiGAMP-based decoding algorithm for massive MIMO unsourced random access, achieving state-of-the-art performance with low complexity.

Contribution

It proposes a new BiSPARCs scheme that integrates bilinear generalized approximate message passing for joint decoding in massive MIMO systems.

Findings

Achieves state-of-the-art performance in massive connectivity scenarios.

Offers comparatively low implementation complexity.

Effectively combines channel estimation, decoding, and interference cancellation.

Abstract

This paper considers the massive MIMO unsourced random access problem in a quasi-static Rayleigh fading setting. The proposed coding scheme is based on a concatenation of a "conventional" channel code (such as, e.g., LDPC) serving as an outer code, and a sparse regression code (SPARC) serving as an inner code. The scheme combines channel estimation, single-user decoding, and successive interference cancellation in a novel way. The receiver performs joint channel estimation and SPARC decoding via an instance of a bilinear generalized approximate message passing (BiGAMP) based algorithm, which leverages the intrinsic bilinear structure that arises in the considered communication regime. The detection step is followed by a per-user soft-input-soft-output (SISO) decoding of the outer channel code in combination with a successive interference cancellation (SIC) step. We show via numerical simulation that the resulting scheme achieves stat-of-the-art performance in the massive connectivity setting, while attaining comparatively low implementation complexity.