On Determining the Number of Preambles in Grant-Free mMTC Uplink to Reduce Collisions

• Main Authors: Jha, Smriti, Srinath, Harini Grama, Mysore Balasubramanya, Naveen
• Format: Conference Proceeding
• Language: English
• Subjects: Closed-form solutions; Internet of Things; Key performance indicator; Massive machine type communications; Monte Carlo methods; Physical layer; Time-frequency analysis
• ISSN: 1558-2612
• DOI: 10.1109/WCNC55385.2023.10118604

Grant-free (GF) access is considered in the uplink for efficiently supporting massive machine type communication (mMTC) scenarios in the Internet of things (IoT). Being a contention-based procedure, GF transmissions consisting of preamble followed by data are susceptible to collisions. This results in an increased number of failed users who retransmit and add to the load on the network. Given that the network is already dense, it is essential to reduce collisions and hence minimize the number of failed users. In this work, a system model for multi-user GF uplink transmission with repetitions is proposed, where the time-frequency resources are divided into transmission opportunity (TO) groups whose size is equal to the number of repetitions adopted by the users. Considering preamble transmissions at the link layer, the key performance indicators (KPIs) corresponding to the per-user and all-user success probabilities of the users in such a system are derived. Further, a method to determine the number of preambles based on the sum of the all-user success probability and the probability of a single user failing in the system is proposed, and closedform expressions for the same are derived. It is demonstrated that our proposed method to find the number of preambles ensures that the collisions (and hence the number of failed users) are reduced considering two scenarios based on the number of users arriving - a) fixed and b) random (following a Poisson distribution). The correctness of our analysis is verified through Monte-Carlo simulations in both the scenarios.