Random Access Based on Maximum Average Distance Code for Massive MTC in Cellular IoT Networks

TL;DR

This paper introduces a novel random access scheme for massive machine-type communications in cellular IoT networks, utilizing a q-ary code with maximum average distance to reduce code ambiguity and improve access success.

Contribution

It proposes a new random access method based on maximum average distance codes and a hypergraph-based decoding approach, addressing code ambiguity in CeRA.

Findings

Significantly increases successful channel access probability

Enhances resource utilization efficiency

Provides an analytical model for the proposed scheme

Abstract

Code-expanded Random Access (CeRA) is a promising technique for supporting mMTC in cellular IoT networks. However, its potentiality is limited by code ambiguity, which results from the inference of a larger number of codewords than those actually transmitted. In this letter, we propose a random access scheme to alleviate this problem by allowing devices to select the preambles to be transmitted considering a q-ary code with maximum average distance. Moreover, a CeRA decoding approach based on hypergraphs is proposed and an analytical model is derived. Numerical results show that the proposed scheme significantly increases the probability of successful channel access as well as resource utilization.