Reed-Muller Sequences for 5G Grant-free Massive Access

TL;DR

This paper introduces second order Reed-Muller sequences for 5G grant-free access, enabling larger user capacity and lower detection complexity, with a noise-resilient detection algorithm to meet ultra-reliable, low-latency requirements.

Contribution

It proposes a novel layered sequence construction and detection algorithm for Reed-Muller sequences, improving detection performance in massive connectivity scenarios.

Findings

Supports larger user space with lower collision probability

Achieves lower detection complexity suitable for 5G

Demonstrates effectiveness through link-level simulations

Abstract

We propose to use second order Reed-Muller (RM) sequence for user identification in 5G grant-free access. The benefits of RM sequences mainly lie in two folds, (i) support of much larger user space, hence lower collision probability and (ii) lower detection complexity. These two features are essential to meet the massive connectivity ($10^7$ links/km$^2$), ultra-reliable and low-latency requirements in 5G, e.g., one-shot transmission ($\leq 1$ms) with $\leq 10^{-4}$ packet error rate. However, the non-orthogonality introduced during sequence space expansion leads to worse detection performance. In this paper, we propose a noise-resilient detection algorithm along with a layered sequence construction to meet the harsh requirements. Link-level simulations in both narrow-band and OFDM-based scenarios show that RM sequences are suitable for 5G.