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