Goal-Oriented Communication for Networked Control Assisted by Reconfigurable Meta-Surfaces
Mohamad Assaad, Touraj Soleymani
TL;DR
The paper addresses how to jointly optimize RIS phase shifts and controller policies in a RIS-assisted networked control system to minimize a quadratic regulation cost across multiple processes. It formalizes a separation-based approach where optimal control actions follow a certainty-equivalent LQR strategy using Kalman-like estimates, and it reduces phase design to a dynamic-programming problem over the phase policy. A tractable suboptimal solution via a semi-definite relaxation (SDP) and Gaussian randomization is proposed, along with a one-step lookahead bound to guide the RIS configuration. Numerical results with a two-pair setup validate that the proposed RIS-aware strategy outperforms random RIS phases, highlighting potential gains in reliability and promptness of closed-loop control in wireless environments. The work demonstrates that goal-oriented communication principles can be effectively instantiated in RIS-assisted control, enabling practical implementations for smart factories, IoT, and autonomous systems.
Abstract
In this paper, we develop a theoretical framework for goal-oriented communication assisted by reconfigurable meta-surfaces in the context of networked control systems. The relation to goal-oriented communication stems from the fact that optimization of the phase shifts of the meta-surfaces is guided by the performance of networked control systems tasks. To that end, we consider a networked control system in which a set of sensors observe the states of a set of physical processes, and communicate this information over an unreliable wireless channel assisted by a reconfigurable intelligent surface with multiple reflecting elements to a set of controllers that correct the behaviors of the physical processes based on the received information. Our objective is to find the optimal control policy for the controllers and the optimal phase policy for the reconfigurable intelligent surface that jointly minimize a regulation cost function associated with the networked control system. We characterize these policies, and also propose an approximate solution based on a semi-definite relaxation technique.