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arXiv · 2412.00513

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

Haochen Li·Xidong Mu·Yuanwei Liu·Yue Chen·Pan Zhiwen
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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.

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Haochen Li, Xidong Mu, Yuanwei Liu, Yue Chen, Pan Zhiwen. 2024-11-30. STAR-RIS Aided Integrated Sensing, Computing, and Communication for Internet of Robotic Things. https://doi.org/10.1109/jiot.2024.3447574

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