An Approach to Preamble Collision Reduction in Grant-Free Random Access with Massive MIMO

TL;DR

This paper introduces a novel method using superpositioned preambles to reduce collision probability in grant-free massive MIMO systems, enhancing success rates without increasing preamble count.

Contribution

It proposes a new superpositioned preamble technique that decreases collision likelihood and improves success probability in grant-free massive MIMO access.

Findings

Superpositioned preambles reduce collision probability.

The approach increases success rate without additional preambles.

Performance confirmed through analysis and simulations.

Abstract

In this paper, we study grant-free random access with massive multiple input multiple output (MIMO) systems. We first show that the performance of massive MIMO based grant-free random access is mainly decided by the probability of preamble collision. The implication of this is that although the number of antennas can be arbitrarily large, the (average) number of successful packet transmissions can be limited by the number of preambles. Then, we propose an approach to preamble collision reduction without increasing the number of preambles using the notion of superpositioned preambles (S-preambles). Since the channel estimation for conjugate beamforming can be carried out when unused S-preambles are known, a simple approach is derived to detect unused S-preambles and its performance is analyzed for a special case (superpositions with 2 preambles). Based on analysis and simulation results, it is confirmed that the proposed approach with S-preambles can increase the success probability with the same spectral efficiency as the conventional approach.