Energy-Efficient Caching and User Selection for Resource-Limited SAGINs in Emergency Communications
Qing Wei, Yingyang Chen, Ziye Jia, Wenle Bai, Tingrui Pei, Qihui Wu
Abstract
The ever-increasing requests of users in emergency communication scenarios lead to high data traffic and transmission delay, posing challenges for resource-limited space-air-ground integrated networks (SAGINs). To address this issue, this paper proposes a joint caching optimization and user selection (JCOUS) problem that leverages unmanned aerial vehicle (UAV) caching to maximize the residual energy of the satellite, considering the limited resources of UAVs. To address the complex time-coupling optimization problem with discrete variables, we propose a primal decomposition method to decouple the problem, and design an energy-efficient user selection algorithm with dynamic caching. Furthermore, to reduce computational complexity and cost, we consider a statistical scenario and maximize the statistical residual energy in the JCOUS problem. Simulation results verify that the proposed scheme can achieve a higher residual energy and fast optimization, thus realizing energy saving and quick decision making especially in large-scale computation-intensive SAGINs.