A Grouping Algorithm for Random Access Networks and Supermartingale Evaluation

Abstract

Wireless communications play a critical role in the applications of Internet of Things (IoT). The Carrier Sense Multiple Access/Collision Avoidance (CSMA/CA) is a well-proven wireless random access protocol. A crucial factor affecting the performance of random access networks is “hidden node collision,” which incurs performance degradation and lower resource utilization. Grouping is an efficient strategy for hidden node avoidance. In current IoT networks, the terminals usually have different traffic load, so load balance should be considered when grouping algorithm is designed. To mitigate hidden nodes and achieve load balance simultaneously, we propose a grouping algorithm based on the game theory. By introducing the supermartingale theory, the delay performance of the completed groups is analyzed. Simulations prove that the proposed algorithm alleviates collision, balances traffic, and promotes the efficient guarantee for Quality of Service (QoS).