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A new concept of center processing unit (CPU)-integrated simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) is proposed, namely computing STAR-RIS. Computation-intensive and delay-sensitive tasks from mobile users can be partially processed at the computing STAR-RIS. We aim to minimize the energy consumption of users and the computing STAR-RIS, and formulate a joint task offloading and transmission resource allocation problem. The solution of this problem is affected by the offloading decision and the amplitude and phase-shift of the computing STAR-RIS. To solve the non-convex problem, we decompose it into two subproblems: 1) For the task offloading subproblem, the offloading decision is optimized utilizing the Karush-Kuhn- Tucker (KKT) conditions; and 2) For the transmission resource allocation subproblem, the transmission-reflection coefficient matrix are optimized via successive convex approximation (SCA). Simulation results show that our proposed algorithm can converge faster and have lower energy consumption than the conventional STAR-RIS. © 2024 IEEE.
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ISSN: 1525-3511
Year: 2024
Language: English
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ESI Highly Cited Papers on the List: 0 Unfold All
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30 Days PV: 1
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