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

Code-expanded Random Access (CeRA) is a promising technique for supporting massive machine-type communications 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 (RA) 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.