We investigate reconfigurable intelligent surface (RIS)-assisted simultaneous wireless information and power transfer (SWIPT) Internet of Things (IoT) networks, where energy-limited IoT devices are overlaid with cellular information users (IUs). IoT devices are wirelessly powered by a RIS-assisted massive multiple-input multiple-output (MIMO) base station (BS), which is simultaneously serving a group of IUs. By leveraging a two-timescale transmission scheme, precoding at the BS is developed based on the instantaneous channel state information (CSI), while the passive beamforming at the RIS is adapted to the slowly-changing statistical CSI. We derive closed-form expressions for the achievable spectral efficiency of the IUs and average harvested energy at the IoT devices, taking the channel estimation errors and pilot contamination into account. Then, a non-convex max-min fairness optimization problem is formulated subject to the power budget at the BS and individual quality of service requirements of IUs, where the transmit power levels at the BS and passive RIS reflection coefficients are jointly optimized. Our simulation results show that the average harvested energy at the IoT devices can be improved by $132\%$ with the proposed resource allocation algorithm. Interestingly, IoT devices benefit from the pilot contamination, leading to a potential doubling of the harvested energy in certain network configurations.

翻译：本文研究可重构智能表面（RIS）辅助的无线信息与功率同传（SWIPT）物联网（IoT）网络，其中能量受限的物联网设备与蜂窝信息用户（IU）共存。物联网设备通过RIS辅助的大规模多输入多输出（MIMO）基站（BS）进行无线供能，该基站同时服务一组信息用户。通过采用双时间尺度传输方案，基站预编码基于瞬时信道状态信息（CSI）设计，而RIS的无源波束成形则适应缓慢变化的统计CSI。在考虑信道估计误差和导频污染的情况下，我们推导了信息用户可达频谱效率与物联网设备平均收集能量的闭式表达式。随后，在基站功率预算和信息用户个体服务质量要求的约束下，构建了非凸的最大-最小公平性优化问题，其中联合优化了基站的发射功率水平与RIS无源反射系数。仿真结果表明，采用所提资源分配算法可使物联网设备的平均收集能量提升132%。有趣的是，物联网设备能够从导频污染中获益，在某些网络配置下收集能量可能翻倍。