Resource Allocation for Secrecy Rate Optimization in UAV-assisted Cognitive Radio Network

Abstract

Cognitive radio (CR) as a key technology of solving the problem of low spectrum utilization has attracted wide attention in recent years. However, due to the open nature of the radio, the communication links can be eavesdropped by illegal user, resulting to severe security threat. Unmanned aerial vehicle (UAV) equipped with signal sensing and data transmission module, can access to the unoccupied channel to improve network security performance by transmitting artificial noise (AN) in CR networks. In this paper, we propose a resource allocation scheme for UAV-assisted overlay CR network. Based on the result of spectrum sensing, the UAV decides to play the role of jammer or secondary transmitter. The power splitting ratio for transmitting secondary signal and AN is introduced to allocate the UAV's transmission power. Particularly, we jointly optimize the spectrum sensing time, the power splitting ratio and the hovering position of the UAV to maximize the total secrecy rate of primary and secondary users. The optimization problem is highly intractable, and we adopt an adaptive inertia coefficient particle swarm optimization (A-PSO) algorithm to solve this problem. Simulation results show that the proposed scheme can significantly improve the total secrecy rate in CR network.