Gaussian Belief Propagation for mmWave Large MIMO Detection with Low-Resolution ADCs

We propose a novel message passing de-quantization (MPDQ) algorithm for low-complexity uplink signal detection in mmWave large multi-user multi-input multi-output (MUMIMO) systems with low-resolution analog-to-digital converters (ADCs) suffering from severe quantization errors. The proposed method consists of a de-quantization (DQ) step based on the Bussgang theorem and a Bayesian multi-user detection (MUD) via Gaussian belief propagation (GaBP), which detects the uplink signal while compensating for the quantized signal distortion. The efficacy is demonstrated by simulation results, which are shown to significantly outperform the current state-of-the-art (SotA) detection designed by Bussgang minimum mean square error (BMMSE) and generalized approximate message passing (GAMP) frameworks in 1-bit quantization, and approach the matched filter bound (MFB) performance.