Secrecy Energy Efficiency Maximization in Space-Air-Ground Internet of Things Networks

Traditional terrestrial communication technologies have struggled to keep up with the growing demands for communication in recent years. As a potential solution, the space-air-ground integrated network has received a lot of attention. However, it also faces many unprecedented security challenges. Compared to traditional key-based methods, physical layer security, which does not depend on upper layer encryption, has gained considerable interest. This paper aims to maximize the secrecy energy efficiency, and considers a space-air-ground Internet of Things network model in which the eavesdropper is an airship. To counter the eavesdropping threat, unmanned aerial vehicles send artificial noise signals to confuse eavesdroppers. The formulated problem is devided into two subproblems of power control and trajectory optimization. Dinkelbach algorithm, successive convex approximation algorithm, and the method of introducing slack variables are employed to transform the non-convex subproblems into convex forms. Simulation results show that our developed algorithm can converge within a few iterations.