UAV-Assisted Intelligent Reflecting Surface Symbiotic Radio System

This paper investigates a symbiotic unmanned aerial vehicle (UAV)-assisted intelligent reflecting surface (IRS) radio system, where the UAV is leveraged to help IRS reflect its own signals base station, and meanwhile enhance transmission by passive beamforming at IRS. First, we consider weighted sum bit error rate (BER) minimization problem among all IRSs jointly optimizing trajectory, phase shift matrix, scheduling, subject minimum primary requirements. To tackle this complicated problem, relaxation-based algorithm proposed. We prove that converged relaxation scheduling variables are binary, which means no reconstruct strategy needed, thus constraints automatically satisfied. Second, fairness BER optimization problem. find method cannot solve since requirements may not be satisfied binary reconstruction operation. address issue, first transform into series of equivalent equality constraints. Then, penalty-based proposed obtain suboptimal solution. Numerical results provided evaluate performance designs under different setups, as compared with benchmarks.