Maxmin Fairness for UAV-Enabled Proactive Eavesdropping With Jamming Over Distributed Transmit Beamforming-Based Suspicious Communications

Abstract

Unmanned aerial vehicle (UAV) plays an important role in wireless communication systems, due to the additional degree of freedom realized from its flexible deployment. Driven by this advantage and considering the security issue, this paper aims to investigate UAV-enabled proactive eavesdropping over distributed transmit beamforming-based suspicious communications. Specifically, for the suspicious system, there are multiple suspicious clusters aiming to communicate with the suspicious destination (D) using mutually orthogonal frequency bands, and distributed transmit beamforming is exploited by each cluster to strengthen the signal receiving quality at D. For the legitimate party, the full-duplex UAV exploits one antenna to jam D and uses the other antenna to overhear the signals of the suspicious clusters concurrently. By resorting to the Laguerre series approximation and the central limit theorem, we first characterize, in closed form, the approximated distributions of the receiving signal-to-interference-noise ratio (SINR) at D and the UAV, which are shown to be very tight. Based on this analysis and considering that the suspicious system works in the delay-limited transmission mode or the delay-sensitive transmission mode, we aim to maximize the minimum eavesdropping success probability of the UAV for those suspicious communications links, by jointly adjusting the UAV’s deployment and jamming power allocations over different frequency bands. The problem is highly non-convex. To tackle this, we develop an alternative optimization framework and further a novel and low-complexity solution in the high SNR regime to the optimization problem. Simulation results show the effectiveness of our proposed schemes compared to competitive benchmarks.