English

Multi-User Data Detection in Massive MIMO with 1-Bit ADCs

Signal Processing 2023-04-03 v1 Information Theory math.IT

Abstract

We provide new analytical results on the uplink data detection in massive multiple-input multiple-output systems with 1-bit analog-to-digital converters. The statistical properties of the soft-estimated symbols (i.e., after linear combining and prior to the data detection process) have been previously characterized only for a single user equipment (UE) and uncorrelated Rayleigh fading. In this paper, we consider a multi-UE setting with correlated Rayleigh fading, where the soft-estimated symbols are obtained by means of maximum ratio combining based on imperfectly estimated channels. We derive a closed-form expression of the expected value of the soft-estimated symbols, which allows to understand the impact of the specific data symbols transmitted by the interfering UEs. Building on this result, we design efficient data detection strategies based on the minimum distance criterion, which are compared in terms of symbol error rate and complexity.

Keywords

Cite

@article{arxiv.2303.18061,
  title  = {Multi-User Data Detection in Massive MIMO with 1-Bit ADCs},
  author = {Amin Radbord and Italo Atzeni and Antti Tölli},
  journal= {arXiv preprint arXiv:2303.18061},
  year   = {2023}
}

Comments

To be presented at IEEE ICASSP 2023

R2 v1 2026-06-28T09:43:10.154Z