We consider a downlink multi-user scenario and investigate the use of reconfigurable intelligent surfaces (RISs) to maximize the dirty-paper-coding (DPC) sum rate of the RIS-assisted broadcast channel. Different from prior works, which maximize the rate achievable by linear precoders, we assume a capacity-achieving DPC scheme is employed at the transmitter and optimize the transmit covariances and RIS reflection coefficients to directly maximize the sum capacity of the broadcast channel. We propose an optimization algorithm that iteratively alternates between optimizing the transmit covariances using convex optimization and the RIS reflection coefficients using Riemannian manifold optimization. Our results show that the proposed technique can be used to effectively improve the sum capacity in a variety of scenarios compared to benchmark schemes.

This paper presents a new Wireless Power Transfer (WPT) approach by aligning the phases of a group of spatially distributed Radio Frequency (RF) transmitters (TX) at the target receiver (RX) device. Our approach can transfer energy over tens of meters and even to targets blocked by obstacles. Compared to popular beamforming based WPTs, our approach leads to a drastically different energy density distribution: the energy density at the target receiver is much higher than the energy density at other locations. Due to this unique energy distribution pattern, our approach offers a safer WPT solution, which can be potentially scaled up to ship a higher level of energy over longer distances. Specifically, we model the energy density distribution and prove that our proposed system can create a high energy peak exactly at the target receiver. Then we conduct detailed simulation studies to investigate how the actual energy distribution is impacted by various important system parameters, including number/topology of transmitters, transmitter antenna directionality, the distance between receiver and transmitters, and environmental multipath. Finally, we build an actual prototype with 17 N210 and 4 B210 Universal Software Radio Peripheral (USRP) nodes, through which we validate the salient features and performance promises of the proposed system.