Modeling and parameter optimization of statistical priority-based multiple access protocol

The Statistical Priority-based Multiple Access Protocol (SPMA) is the de facto standard for Tactical Target Network Technology (TTNT) and has also been implemented in ad hoc networks. In this paper, we present a non-preemptive M/M/1/K queuing model to analyze the performance of different priorities in SPMA in terms of average packet loss rate and delay. And based on this queuing model, we designed a percentile scoring system combined with Q-learning algorithm to optimize the protocol parameters. The simulation results show that our theoretical model is closely matched with the reality, and the proposed algorithm improves the efficiency and accuracy in finding the optimal parameter set of SPMA protocol.