Joint Resource Optimization Over Licensed and Unlicensed Spectrum in Spectrum Sharing UAV Networks Against Jamming Attacks

TL;DR

This paper proposes a joint resource optimization framework for spectrum sharing UAV networks that enhances sum rate performance while addressing security threats from jamming attacks, through iterative algorithms for power, subchannel, and trajectory design.

Contribution

It introduces a novel joint optimization approach combining power, subchannel, and trajectory design for spectrum sharing UAV networks under jamming threats, with a low-complexity iterative solution.

Findings

Significant sum rate improvement over benchmark schemes.

Effective anti-jamming spectrum sharing strategy.

Validated through extensive simulations.

Abstract

Unmanned aerial vehicle (UAV) communication is of crucial importance in realizing heterogeneous practical wireless application scenarios. However, the densely populated users and diverse services with high data rate demands has triggered an increasing scarcity of UAV spectrum utilization. To tackle this problem, it is promising to incorporate the underutilized unlicensed spectrum with the licensed spectrum to boost network capacity. However, the openness of unlicensed spectrum makes UAVs susceptible to security threats from potential jammers. Therefore, a spectrum sharing UAV network coexisting with licensed cellular network and unlicensed Wi-Fi network is considered with the anti-jamming technique in this paper. The sum rate maximization of the secondary network is studied by jointly optimizing the transmit power, subchannel allocation, and UAV trajectory. We first decompose the challenging non-convex problem into two subproblems, 1) the joint power and subchannel allocation and 2) UAV trajectory design subproblems. A low-complexity iterative algorithm is proposed in a alternating optimization manner over these two subproblems to solve the formulated problem. Specifically, the Lagrange dual decomposition is exploited to jointly optimize the transmit power and subchannel allocation iteratively. Then, an efficient iterative algorithm capitalizing on successive convex approximation is designed to get a suboptimal solution for UAV trajectory. Simulation results demonstrate that our proposed algorithm can significantly improve the sum transmission rate compared with the benchmark schemes.