Preamble Parallelization vs. Colliding Preamble Reuse: Intelligent Massive Random Access Control for mMTC System in Smart Cities
Ziming Guo, Xu Zhu, Jie Cao, Yufei Jiang, Vincent K. N. Lau, Sumei Sun · 2024
The integration of Internet-of-Things (IoT) and the fifth-generation (5G) networks presents challenges due to low access efficiency caused by massive random access (RA) requests. To this end, both preamble parallelization (PP) and colliding preambles reuse (CPR) modes are proposed as critical RA control methods to enhance access performance. In this paper, we aim to maximize the random access efficiency (RAE) in a smart city scenario to determine the optimal control mode selection between the PP and CPR over the device heterogeneity with limited RA resources. We establish an access order-backoff window (AOBW) mapping model, where RA requirements are mapped onto the backoff time. It offers greater flexibility of backoff window size than previous work to guarantee diverse application and service requirements. Thanks to the derived closed-form expressions of the actual RAE, an RAE maximization algorithm is developed, which optimizes performance across both PP and CPR modes, achieving optimal performance in access delay and access throughput.