AoI-Aware Multiple Access for Unmanned Swarm Network: A Poisson Evolutionary Game Approach

In the context of the space-air-ground integrated networks (SAGIN), unmanned swarms facilitate the collaborative operation of unmanned aerial vehicles (UAVs) to accomplish shared objectives through a decentralized ad hoc network architecture. However, the dynamic population size and topology of the unmanned swarm network (USNet) pose significant challenges for the design of multiple access mechanisms that aim to minimize the age of information (AoI). In this study, we introduce a Poisson evolutionary game (PEG) framework that models the population changes using a Poisson process and describes the strategic interactions between an individual and the population as an evolutionary process. We provide a mathematical characterization of the Evolutionary Stable Strategies (ESS) within this framework and theoretically analyze their existence under relatively mild conditions. Furthermore, we propose a replicator dynamic-based algorithm to address the game, and present numerical results that demonstrate the algorithm's convergence performance and elucidate the relationship between the game's design parameters and the ESS point. Index Terms-Multiple access game, unmanned swarm, age of information, evolutionary game, Poisson process.