WMMSE-Based Rate Maximization for RIS-Assisted MU-MIMO Systems

Reconfigurable intelligent surface (RIS) technology, given its ability to favorably modify wireless communication environments, will play a pivotal role in the evolution of future communication systems. This paper proposes rate maximization techniques for both single-user and multiuser MIMO systems, based on the well-known weighted minimum mean square error (WMMSE) criterion. Using a suitable weight matrix, the WMMSE algorithm tackles an equivalent weighted mean square error (WMSE) minimization problem to achieve the sum-rate maximization. By considering a more practical RIS system model that employs a tensor-based representation enforced by the electromagnetic behavior exhibited by the RIS panel, we detail both the sum-rate maximizing and WMSE minimizing strategies for RIS phase shift optimization by deriving the closed-form gradient of the WMSE and the sum-rate with respect to the RIS phase shift vector. Our simulations reveal that the proposed rate maximization technique, rooted in the WMMSE algorithm, exhibits superior performance when compared to other benchmarks.

A Deep Reinforcement Learning Approach for Autonomous Reconfigurable Intelligent Surfaces

A reconfigurable intelligent surface (RIS) is a prospective wireless technology that enhances wireless channel quality. An RIS is often equipped with passive array of elements and provides cost and power-efficient solutions for coverage extension of wireless communication systems. Without any radio frequency (RF) chains or computing resources, however, the RIS requires control information to be sent to it from an external unit, e.g., a base station (BS). The control information can be delivered by wired or wireless channels, and the BS must be aware of the RIS and the RIS-related channel conditions in order to effectively configure its behavior. Recent works have introduced hybrid RIS structures possessing a few active elements that can sense and digitally process received data. Here, we propose the operation of an entirely autonomous RIS that operates without a control link between the RIS and BS. Using a few sensing elements, the autonomous RIS employs a deep Q network (DQN) based on reinforcement learning in order to enhance the sum rate of the network. Our results illustrate the potential of deploying autonomous RISs in wireless networks with essentially no network overhead.

WiThRay: A Versatile Ray-Tracing Simulator for Smart Wireless Environments

This paper presents the development and evaluation of WiThRay, a new wireless three-dimensional ray-tracing (RT) simulator. RT-based simulators are widely used for generating realistic channel data by combining RT methodology to get signal trajectories and electromagnetic (EM) equations, resulting in generalized channel impulse responses (CIRs). This paper first provides a comprehensive comparison on methodologies of existing RT-based simulators. We then introduce WiThRay, which can evaluate the performance of various wireless communication techniques such as channel estimation/tracking, beamforming, and localization in realistic EM wave propagation. WiThRay implements its own RT methodology, the bypassing on edge (BE) algorithm, that follows the Fermat's principle and has low computational complexity. The scattering ray calibration in WiThRay also provides a precise solution in the analysis of EM propagation. Different from most of the previous RT-based simulators, WiThRay incorporates reconfigurable intelligent surfaces (RIS), which will be a key component of future wireless communications. We thoroughly show that the channel data from WiThRay match sufficiently well with the fundamental theory of wireless channels. The virtue of WiThRay lies in its feature of not making any assumption about the channel, like being slow/fast fading or frequency selective. A realistic wireless environment, which can be conveniently simulated via WiThRay, naturally defines the physical properties of the wireless channels. WiThRay is open to the public, and anyone can exploit this versatile simulator to develop and test their communications and signal processing techniques.

Exploiting Gold Nanoparticles for Secure Visible Light Communications

Visible light is a proper spectrum for secure wireless communications because of its high directivity and impermeability. To make visible light communication (VLC) even more secure, we propose to exploit recently synthesized gold nanoparticles (GNPs) with chiroptical properties for circularly polarized light. Carefully synthesized GNPs can differentially absorb and retard the left and right circularly polarized light, and a GNP plate made by judiciously stacking many GNPs can elaborately manipulate the amplitudes and phases of left and right circularly polarized light. In the proposed VLC system with multiple transmitters, each transmitter is equipped with a GNP plate and a linear polarizer while the legitimate receiver is equipped with only a linear polarizer. A new VLC channel model is first developed by representing the effect of GNP plates and linear polarizers in the circular polarization domain. Based on the new channel model, the angles of linear polarizers at the transmitters and legitimate receiver are optimized considering the effect of GNP plates to increase the secrecy rate in wiretapping scenarios. Simulation results verify that when the transmitters are equipped with the GNP plates, the secrecy rate around the legitimate receiver is significantly improved due to the chiroptical properties of GNP plates even if a nearby eavesdropper sets the linear polarizer angle same as the legitimate receiver.