In this letter, we study the resource allocation for a multiuser intelligent reflecting surface (IRS)-aided simultaneous wireless information and power transfer (SWIPT) system. Specifically, a multi-antenna base station (BS) transmits energy and information signals simultaneously to multiple energy harvesting receivers (EHRs) and information decoding receivers (IDRs) assisted by an IRS. Under this setup, we introduce a multi-objective optimization (MOOP) framework to investigate the fundamental trade-off between the data sum-rate maximization and the total harvested energy maximization, by jointly optimizing the energy/information beamforming vectors at the BS and the phase shifts at the IRS. This MOOP problem is first converted to a single-objective optimization problem (SOOP) via the $\epsilon$-constraint method and then solved by majorization minimization (MM) and inner approximation (IA) techniques. Simulation results unveil a non-trivial trade-off between the considered competing objectives, as well as the superior performance of the proposed scheme as compared to various baseline schemes.
翻译:在这封信中,我们研究了多用户智能反映表面(IRS)辅助的同步无线信息和电力传输系统的资源分配情况,具体来说,一个多保险基站(BS)同时将能源和信息信号传送给多个能源采集接收器(EHRs)和由IRS协助的信息解码接收器(IDRs)。在这个设置下,我们引入了一个多目标优化框架,以调查数据总和最大化和总收获的能源最大化之间的根本权衡,办法是联合优化BS的能源/信息成型矢量和IRS的阶段转移。MOP问题首先通过美元-约束法转换为单一目标优化问题,然后通过主要最小化(MM)和内部近距离(IA)技术加以解决。模拟结果揭示了被认为相互竞争的目标之间的非三重权衡,以及拟议计划相对于各种基线计划的优异性表现。