Novel framework for physical-layer secrecy and network secrecy energy efficiency of UAV-assisted device-to-device communication
TL;DR
Simulation results show that the recommended approach can effectively reduce co-channel interference, improve the energy efficiency of network privacy, and achieve a balance between network energy consumption and secure communication performance.
Abstract
Wireless networks are anticipated to continue connecting billions of devices and producing enormous amounts of data with the next sixth-generation (6G) technologies, propelling the development of artificial intelligence applications in a variety of industries. Unmanned aerial vehicles have shown promise in this regard as a way to deal with the problems brought on by the expanding environment. UAVs are especially well-suited for delivering on-demand services to mobile devices because of their special qualities, which include their mobility, flexibility, and capacity to create line-of-sight communication links. This is especially true in areas with limited terrestrial infrastructure, such as hot areas and disaster communication. Therefore, by acting as relaying points, aerial base stations, and data collectors, UAVs may greatly increase the capacity and reach of networks. To address the challenges of energy limitations, spectrum scarcity, and severe co-channel interference in device-to-device (D2D) communication networks supporting UAVs in passive eavesdropping environments, the concept of secrecy energy-efficiency was introduced by considering each user’s privacy level and transmission power limitations. Based on physical layer secure transmission theory, the common problem of optimizing spectrum multiplexing and energy management strategies to maximize the energy efficiency of network secrecy was studied. A resource allocation algorithm combining the two algorithms was proposed to ensure the convergence of the original problem to a global optimal solution using the Dinkelbach algorithm and to transform the non-convex optimization problem into a geometric planning problem using the convex approximation algorithm. The problem was non-linear and non-convex. Simulation results show that the recommended approach can effectively reduce co-channel interference, improve the energy efficiency of network privacy, and achieve a balance between network energy consumption and secure communication performance.