STAR-RIS Aided Integrated Sensing, Computing, and Communication for Internet of Robotic Things

TL;DR

This paper proposes a STAR-RIS aided integrated sensing, computing, and communication framework for the Internet of Robotic Things, optimizing beamformers and RIS coefficients to maximize computation rate and improve system performance.

Contribution

It introduces a novel STAR-RIS assisted ISCC IoRT system with an optimization framework and solution algorithms, enhancing computation rate over benchmarks.

Findings

The proposed system outperforms benchmark schemes in simulation.

The optimization algorithm converges to a stationary point.

STAR-RIS significantly improves system sum computation rate.

Abstract

A simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) aided integrated sensing, computing, and communication (ISCC) Internet of Robotic Things (IoRT) framework is proposed. Specifically, the full-duplex (FD) base station (BS) simultaneously receives the offloading signals from decision robots (DRs) and carries out target robot (TR) sensing. A computation rate maximization problem is formulated to optimize the sensing and receive beamformers at the BS and the STAR-RIS coefficients under the BS power constraint, the sensing signal-to-noise ratio constraint, and STAR-RIS coefficients constraints. The alternating optimization (AO) method is adopted to solve the proposed optimization problem. With fixed STAR-RIS coefficients, the sub-problem with respect to sensing and receiving beamformer at the BS is tackled with the weighted minimum mean-square error method. Given beamformers at the BS, the sub-problem with respect to STAR-RIS coefficients is tacked with the penalty method and successive convex approximation method. The overall algorithm is guaranteed to converge to at least a stationary point of the computation rate maximization problem. Our simulation results validate that the proposed STAR-RIS aided ISCC IoRT system can enhance the sum computation rate compared with the benchmark schemes.