Energy-Efficient Resource Allocation in UAV-Enabled Detection and Communication Systems
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This paper investigates the problem of resource allocation for unmanned aerial vehicle (UAV) enabled joint radar and communication systems with rate-splitting multiple access (RSMA). In the considered system, UAV serves as a aerial base station to simultaneously communicate with multiple users and probe signals to targets of interest. By virtue of using linearly precoded rate splitting at the transmitter and successive interference cancellation at the receivers, RSMA is introduced as a promising paradigm to manage interference as well as enhance spectrum and energy efficiency. To maximize the energy efficiency of UAV networks, the deployment location and the beamforming matrix are jointly optimized under the constraints of power budget, transmission rate and approximation error. To solve the formulated non-convex problem (P1) efficiently, we decompose it into the UAV deployment subproblem (P2) and the beamforming optimization subproblem (P3). Then, we invoke the successive convex approximation and difference-of-convex programming as well as Dinkelbach methods to transform the intractable subproblems P2 and P3 into convex ones at each iteration. Next, an alternating algorithm is designed to solve the non-linear and non-convex problem (P1) in an efficient manner, while the corresponding complexity is analyzed as well. Finally, simulation results reveal that proposed algorithm with RSMA is superior to orthogonal multiple access and power-domain non-orthogonal multiple access in terms of power consumption and energy efficiency.
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