IRS辅助的共生无线电系统鲁棒优化算法设计

Robust Optimization Algorithm Design for IRS-Aided Symbiotic Radio System

共生无线电技术可用于提高频谱效率与能量效率,但其中物联网接收机的接收信号强度较弱,在共生无线电系统中部署智能反射表面是针对该问题的一种有效解决方案。首先,在完美信道状态信息可知时,考虑基站信息速率要求、反射单元相移的约束、反向散射设备的解码顺序与反射系数的约束,联合优化无源波束赋形与反向散射设备的反射系数来最大化所有反向散射设备中最小的吞吐量。然后,考虑到系统中的实时完美信道状态信息很难获得的问题,提出了针对不完美信道状态信息的鲁棒优化算法。仿真结果验证了智能反射表面可使共生无线电系统性能大幅提升,相较于保守方法,所提的鲁棒优化算法可降低不完美信道状态信息造成的性能下降。

Symbiotic radio(SR)technology can be used to improve spectral efficiency and energy efficiency.However,seeing that the received signal at the Internet of Things(IoT)receiver is weak,it is a promising solution to deploy intelligent reflecting surface(IRS)in the SR system.Firstly,when perfect channel state information(CSI)is known,considering the rate requirement of the information from the base station,the phase shift constraint of the reflecting element,the decoding order and the reflection coefficient constraint of backscatter devices(BD),the passive beamforming and the reflection coefficient of BDs are jointly optimized to maximize the minimum throughput among all BDs.Then,considering the problem that it is hard to obtain the real-time perfect CSI in the system,a robust optimization algorithm for the imperfect CSI is proposed.The simulation results show that IRS can be used to improve the performance of the SR system greatly.Compared with the conservative method,the proposed robust optimization algorithm can reduce the performance degradation caused by the imperfect CSI.