Analysis of Preamble Collisions in Satellite-Based Internet of Things Using Static Floor Field

Random access protocols play a pivotal role in the development of Satellite-based Internet of Things (S-IoT). However, existing research often inadequately addresses the rapid increase in device numbers, leading to theoretical models that unconvincingly simulate group behavior based on single-device behavior. Instead, we employ the static floor field method, traditionally used to analyze the evacuation of large numbers of pedestrians from confined spaces, to investigate the competition dynamics for limited preambles among numerous devices within the S-IoT system. This approach offers significant advantages in capturing dynamics and ensuring scalability during massive interactive sessions. Specifically, we extend the analysis model, based on the static floor field method, to address the issue of preamble collisions among a large number of IoT devices. The data obtained from this method closely align with the results from a system-level simulation platform, substantiating the accuracy and effectiveness of our analytical approach. Consequently, the analytical and predictive capabilities of the proposed method lead to the development of intelligent preamble resource allocation strategies based on reinforcement learning, thereby enhancing the overall performance of the S-IoT system. The efficacy of the proposed strategy is further validated by results derived from a simulation platform using authentic orbital data.