期刊
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS
卷 20, 期 9, 页码 5769-5785出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TWC.2021.3070014
关键词
Unmanned aerial vehicles; Optimization; Bit error rate; Symbiosis; Array signal processing; Trajectory; Signal to noise ratio; Intelligent reflecting surface (IRS); unmanned aerial vehicle (UAV); phase shift optimization; UAV trajectory optimization
资金
- National Natural Science Foundation of China [U1936201, 61941115, 61971128]
- National Key Research and Development Program of China [2020YFB1804901]
- FDCT [0108/2020/A]
- Open Research Fund of National Mobile Communications Research Laboratory, Southeast University [2021D15]
- U.S. National Science Foundation [ECCS-2030029]
This paper investigates a symbiotic UAV-assisted IRS radio system, proposing relaxation-based and penalty-based algorithms to solve the weighted sum BER minimization problem and fairness BER optimization problem. Numerical results are provided for performance evaluation compared to benchmarks.
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.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据