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Generalized Group Selection Strategies for Self-sustainable RIS-aided Communication

Lakshmikanta Sau, Priyadarshi Mukherjee, Sasthi C. Ghosh

TL;DR

This work develops generalized, order-statistics–based group selection strategies for self-sustainable RIS-aided D2D communications under spatially correlated channels. It jointly analyzes PS and TS energy harvesting, derives energy- and rate-based bounds, and delivers outage expressions for random, SNR-based, and energy-based selection schemes. By leveraging both high-order statistics and extreme value theory, it provides exact and asymptotic performance characterizations and demonstrates significant gains over random grouping in throughputs and outage performance. The approach offers practical design insights for RIS grouping, EH parameters, and large-scale RIS (LIS) deployments with energy constraints.

Abstract

Reconfigurable intelligent surface (RIS) is a cutting-edge communication technology that has been proposed as aviable 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.

Generalized Group Selection Strategies for Self-sustainable RIS-aided Communication

TL;DR

This work develops generalized, order-statistics–based group selection strategies for self-sustainable RIS-aided D2D communications under spatially correlated channels. It jointly analyzes PS and TS energy harvesting, derives energy- and rate-based bounds, and delivers outage expressions for random, SNR-based, and energy-based selection schemes. By leveraging both high-order statistics and extreme value theory, it provides exact and asymptotic performance characterizations and demonstrates significant gains over random grouping in throughputs and outage performance. The approach offers practical design insights for RIS grouping, EH parameters, and large-scale RIS (LIS) deployments with energy constraints.

Abstract

Reconfigurable intelligent surface (RIS) is a cutting-edge communication technology that has been proposed as aviable 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.
Paper Structure (27 sections, 7 theorems, 90 equations, 5 figures, 2 tables)

This paper contains 27 sections, 7 theorems, 90 equations, 5 figures, 2 tables.

Table of Contents

  1. Introduction
  2. System Model
  3. Network Model
  4. RIS Characterization
  5. PS Configuration
  6. TS Configuration
  7. Channel Model
  8. Energy Harvesting Model
  9. Order-Based Selection and Extreme Value Theory
  10. System Characterization
  11. PS Configuration
  12. TS Configuration
  13. Composite Channel Characterization
  14. Proposed Group Selection Strategies
  15. Random Group Selection (RGS)
  16. ...and 12 more sections

Key Result

Theorem 1

By considering a linear EH model and assuming $\rho$ to be equal for all the $M$ reflecting elements of $R_i$, we have where $\eta= \frac{\rho_L E_{l,PS} \times d_{R_i,D}^{-\alpha}}{T_s \sigma^2_0 \sum_{i=1}^{M}|{\Tilde{h_i}}|^2 }|g_c|^2|h_c|^2$ and $R_{\rm req}$ is the application-specific minimum required data rate.

Figures (5)

  • Figure 1: Considered system model.
  • Figure 2: Validation of concept for different SNR thresholds. Variation of outage with (a) SNR, and (b) inter-patch distance.
  • Figure 3: Impact of (a) $\rho$ and $\zeta$ on data rate. Variation of (b) $\rho$, and (c) $\zeta$ with outage performance for different Rician values.
  • Figure 4: (a) Impact of the SBGS's $k$-th selection, (b) Comparison of the proposed and an existing scheme, and (c) Impact of EVT in SBGS.
  • Figure 5: Variation of $P_{\rm tx}$ with energy outage in (a) a linear EH model and (b) a nonlinear EH model.

Theorems & Definitions (14)

  • Theorem 1
  • proof
  • Theorem 2
  • proof
  • Theorem 3
  • proof
  • Theorem 4
  • proof
  • Theorem 5
  • proof
  • ...and 4 more