RIS-Enhanced Semantic-Aware Sensing, Communication, Computation, and Control for Internet of Things

The joint design of sensing, communication, computing, and control (SC<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup>) is crucial for supporting environment-aware Industrial Internet of Things (IIoT) applications. Considering the uncontrollable wireless propagation environments and limited spectrum resources, wireless communication performance often becomes the primary design bottleneck for such an integrated system. To address this challenge, this paper presents a design framework for reconfigurable intelligent surface (RIS)-enhanced semantic-aware SC<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> networks, where RIS and semantic communication technologies are employed to improve wireless communication efficiency. To facilitate real-time closed-loop control, we further formulate a weighted sum execution latency minimization problem, while imposing constraints on maximum execution latency and energy consumption of individual IoT device, as well as minimum information entropy to meet specific control requirements measured by linear quadratic regulator cost. In addition, the design framework aims at optimizing bandwidth allocation, RIS phase shift matrix, time scheduling, transmit power, and CPU-cycle frequency for IoT devices and the base station (BS). To handle the coupled multi-dimensional optimization variables, the block coordinate descent method is utilized to decompose the formulated problem into more tractable subproblems, which are then solved using a penalty-function-based approach and geometric programming technique. Simulation results demonstrate the performance advantages achieved by our proposed method compared to several benchmark approaches. Additionally, we explore the impact of various parameters on SC<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> systems, offering deeper insights and meaningful research observations.