Impact of Interference Subtraction on Grant-Free Multiple Access with Massive MIMO

TL;DR

This paper analyzes the impact of imperfect channel estimation on coded random access in massive MIMO systems and proposes a new signal processing algorithm to improve performance in grant-free multiple access scenarios.

Contribution

It provides an analysis of interference subtraction effects under imperfect channel estimation and introduces a novel signal processing algorithm for CRA in massive MIMO.

Findings

Imperfect channel estimation affects interference cancellation performance.

The proposed algorithm enhances CRA performance in massive MIMO.

Analysis guides future design of scalable access schemes.

Abstract

The design of highly scalable multiple access schemes is a main challenge in the evolution towards future massive machine-type communications, where reliability and latency constraints must be ensured to a large number of uncoordinated devices. In this scenario, coded random access (CRA) schemes, where successive interference cancellation algorithms allow large improvements with respect to classical random access protocols, have recently attracted an increasing interest. Impressive performance can be potentially obtained by combining CRA with massive multiple input multiple output (MIMO). In this paper we provide an analysis of such schemes focusing on the effects of imperfect channel estimation on successive interference cancellation. Based on the analysis we then propose an innovative signal processing algorithm for CRA in massive MIMO systems.