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UAV-Assisted Intelligent Reflecting Surface Symbiotic Radio System

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Document pages: 32 pages

Abstract: This paper investigates a symbiotic unmanned aerial vehicle (UAV)-assistedintelligent reflecting surface (IRS) radio system, where the UAV is leveragedto help the IRS reflect its own signals to the base station, and meanwhileenhance the UAV transmission by passive beamforming at the IRS. First, weconsider the weighted sum bit error rate (BER) minimization problem among allIRSs by jointly optimizing the UAV trajectory, IRS phase shift matrix, and IRSscheduling, subject to the minimum primary rate requirements. To tackle thiscomplicated problem, a relaxation-based algorithm is proposed. We prove thatthe converged relaxation scheduling variables are binary, which means that noreconstruct strategy is needed, and thus the UAV rate constraints areautomatically satisfied. Second, we consider the fairness BER optimizationproblem. We find that the relaxation-based method cannot solve this fairnessBER problem since the minimum primary rate requirements may not be satisfied bythe binary reconstruction operation. To address this issue, we first transformthe binary constraints into a series of equivalent equality constraints. Then,a penalty-based algorithm is proposed to obtain a suboptimal solution.Numerical results are provided to evaluate the performance of the proposeddesigns under different setups, as compared with benchmarks.

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