Generalized Group Selection Strategies for Self-Sustainable RIS-Aided Communication

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Abstract
Reconfigurable intelligent surface (RIS) is a cutting-edge communication technology that has been proposed as a viable option for beyond fifth-generation wireless communication networks. This paper investigates various group selection strategies in the context of grouping-based self-sustainable RIS-aided device-to-device (D2D) communication with spatially correlated wireless channels. Specifically, we consider both power splitting (PS) and time switching (TS) configurations, of the self-sustainable RIS to analyze the system performance and propose appropriate bounds on the choice of system parameters. The analysis takes into account a simplified linear energy harvesting (EH) model as well as a practical non-linear EH model. Based on the application requirements, we propose various group selection strategies at the RIS. Notably, each strategy schedules the k-th best available group at the RIS based on the end-to-end signal-to-noise ratio (SNR) and also the energy harvested at a particular group of the RIS. Accordingly, by using tools from high order statistics, we derive analytical expressions for the outage probability of each selection strategy. Moreover, by applying the tools from extreme value theory, we also investigate an asymptotic scenario, where the number of groups available for selection at an RIS approaches infinity. The nontrivial insights obtained from this approach is especially beneficial in applications like large intelligent surface-aided wireless communication. Finally, the numerical results demonstrate the importance and benefits of the proposed approaches in terms of metrics such as the data throughput and the outage (both data and energy) performance.

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