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Energy Efficiency Optimization for Mutual-Coupling-Aware Wireless Communication System based on RIS-enhanced SWIPT

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journal contribution
posted on 2023-03-27, 10:59 authored by R Ma, J Tang, X Zhang, KK Wong, JA Chambers
The widespread deployment of the Internet of Things (IoT) is promoting interest in simultaneous wireless information and power transfer (SWIPT), the performance of which can be further improved by employing a reconfigurable intelligent surface (RIS). In this paper, we propose a novel RIS-enhanced SWIPT system built on an electromagnetic-compliant framework. The mutual-coupling effects in the whole system are presented explicitly. Moreover, the reconfigurability of RIS is no longer expressed by the reflection-coefficient matrix but by the impedances of the tunable circuit. For comparison, both the no-coupling and the coupling-awareness cases are discussed. In particular, the energy efficiency (EE) is maximized by cooperatively optimizing the impedance parameters of the RIS elements as well as the active beamforming vectors at the base station (BS). For the coupling-awareness case, the considered problem is split into several sub-problems and solved alternatively due to its nonconvexity. Firstly, it is transformed into a more solvable form by applying the Neuman series approximation, which can be resolved iteratively. Then an alternative optimization (AO) framework and semi-definite relaxation (SDR), successive convex approximation (SCA), and Dinkelbach’s algorithm are applied to solve each sub-problem decomposed from it. Owning to the similarity between the two cases, the no-coupling one can be viewed as a reduced form of the coupling case and thus solved through a similar approach. Numerical results reveal the influence of mutual-coupling effects on the EE, especially in the RIS with closely spaced elements. In addition, physical beam designs are presented to demonstrate how the RIS assists SWIPT through various reflecting states in different conditions.


10.13039/501100001809-National Natural Science Foundation of China (Grant Number: 62222105)


Author affiliation

School of Engineering, University of Leicester


  • AM (Accepted Manuscript)

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IEEE Internet of Things Journal


Institute of Electrical and Electronics Engineers (IEEE)



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