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Dynamic Energy-Saving Design for Double-Faced Active RIS Assisted Communications with Perfect/Imperfect CSI

Yang Cao, Wenchi Cheng, Jingqing Wang, Wei Zhang

TL;DR

The paper tackles energy-efficient operation of double-faced active RIS (DFA-RIS) to achieve full-space coverage while mitigating the high energy cost of active components. It proposes a sub-array based DFA-RIS architecture that enables dynamic on/off control of reflection amplifiers (RAs) across sub-arrays, and jointly optimizes transmit beamforming, DFA-RIS configuration, and RA operating patterns to maximize energy efficiency. For perfect CSI, a penalty dual decomposition (PDD) alternating optimization (AO) algorithm is developed, while for imperfect CSI a constrained stochastic majorization-minimization (CSMM) AO algorithm is proposed to handle stochastic channels. Simulation results show substantial EE gains over fully-connected DFA-RIS, single-sided active RIS, and passive STAR-RIS, validating the effectiveness of the sub-array energy-saving approach and the proposed optimization frameworks in multiuser MISO settings.

Abstract

Although the emerging reconfigurable intelligent surface (RIS) paves a new way for next-generation wireless communications, it suffers from inherent flaws, i.e., double-fading attenuation effects and half-space coverage limitations. The state-of-the-art double-face active (DFA)-RIS architecture is proposed for significantly amplifying and transmitting incident signals in full-space. Despite the efficacy of DFA-RIS in mitigating the aforementioned flaws, its potential drawback is that the complex active hardware also incurs intolerable energy consumption. To overcome this drawback, in this paper we propose a novel dynamic energy-saving design for the DFA-RIS, called the sub-array based DFA-RIS architecture. This architecture divides the DFA-RIS into multiple sub-arrays, where the signal amplification function in each sub-array can be activated/deactivated dynamically and flexibly. Utilizing the above architecture, we develop the joint optimization scheme based on transmit beamforming, DFA-RIS configuration, and reflection amplifier (RA) operating pattern to maximize the energy efficiency (EE) of the DFA-RIS assisted multiuser MISO system considering the perfect/imperfect channel state information (CSI) case. Then, the penalty dual decomposition (PDD) based alternating optimization (AO) algorithm and the constrained stochastic majorization-minimization (CSMM) based AO algorithm address non-convex problems in the perfect/imperfect CSI case, respectively. Simulation results verified that our proposed sub-array based DFA-RIS architecture can benefit the EE of the system more than other RIS architectures.

Dynamic Energy-Saving Design for Double-Faced Active RIS Assisted Communications with Perfect/Imperfect CSI

TL;DR

The paper tackles energy-efficient operation of double-faced active RIS (DFA-RIS) to achieve full-space coverage while mitigating the high energy cost of active components. It proposes a sub-array based DFA-RIS architecture that enables dynamic on/off control of reflection amplifiers (RAs) across sub-arrays, and jointly optimizes transmit beamforming, DFA-RIS configuration, and RA operating patterns to maximize energy efficiency. For perfect CSI, a penalty dual decomposition (PDD) alternating optimization (AO) algorithm is developed, while for imperfect CSI a constrained stochastic majorization-minimization (CSMM) AO algorithm is proposed to handle stochastic channels. Simulation results show substantial EE gains over fully-connected DFA-RIS, single-sided active RIS, and passive STAR-RIS, validating the effectiveness of the sub-array energy-saving approach and the proposed optimization frameworks in multiuser MISO settings.

Abstract

Although the emerging reconfigurable intelligent surface (RIS) paves a new way for next-generation wireless communications, it suffers from inherent flaws, i.e., double-fading attenuation effects and half-space coverage limitations. The state-of-the-art double-face active (DFA)-RIS architecture is proposed for significantly amplifying and transmitting incident signals in full-space. Despite the efficacy of DFA-RIS in mitigating the aforementioned flaws, its potential drawback is that the complex active hardware also incurs intolerable energy consumption. To overcome this drawback, in this paper we propose a novel dynamic energy-saving design for the DFA-RIS, called the sub-array based DFA-RIS architecture. This architecture divides the DFA-RIS into multiple sub-arrays, where the signal amplification function in each sub-array can be activated/deactivated dynamically and flexibly. Utilizing the above architecture, we develop the joint optimization scheme based on transmit beamforming, DFA-RIS configuration, and reflection amplifier (RA) operating pattern to maximize the energy efficiency (EE) of the DFA-RIS assisted multiuser MISO system considering the perfect/imperfect channel state information (CSI) case. Then, the penalty dual decomposition (PDD) based alternating optimization (AO) algorithm and the constrained stochastic majorization-minimization (CSMM) based AO algorithm address non-convex problems in the perfect/imperfect CSI case, respectively. Simulation results verified that our proposed sub-array based DFA-RIS architecture can benefit the EE of the system more than other RIS architectures.
Paper Structure (28 sections, 1 theorem, 70 equations, 8 figures, 3 algorithms)

This paper contains 28 sections, 1 theorem, 70 equations, 8 figures, 3 algorithms.

Table of Contents

  1. Introduction
  2. The Dynamic Energy-saving Design for DFA-RIS And System Model
  3. The Dynamic Energy-Saving Design for DFA-RIS
  4. Signal Model of DFA-RIS Based on Sub-Array
  5. System Model
  6. Power Consumption Model And Problem Formulation
  7. Power Consumption Model of Sub-Array Based DFA-RIS
  8. Problem Formulation
  9. The Case of Perfect CSI
  10. The Case of Imperfect CSI
  11. PDD-Based Alternating Optimization In The Case Of Perfect CSI
  12. Fractional Programming Transform
  13. Update $\boldsymbol{\rm {w}}$, $\boldsymbol{\rm {\gamma}}$, And $\boldsymbol{\rm {\nu}}$
  14. Update auxiliary variables $\boldsymbol{\rm {\gamma}}$ and $\boldsymbol{\rm {\nu}}$
  15. Update transmit beamforming $\boldsymbol{\rm {w}}$
  16. ...and 13 more sections

Key Result

Theorem 1

Let $\boldsymbol{\rm {U}}\in\mathbb{C}^{M\times M}$ is a Hermitian matrix and $\boldsymbol{\rm {\breve U}}\in\mathbb{C}^{M\times M}$ is another Hermitian matrix such that $\boldsymbol{\rm {\breve U}}\succeq\boldsymbol{\rm {U}}$. For any given point $\boldsymbol{\rm {d}}^{(i)}\in\mathbb{C}^{M\times 1

Figures (8)

  • Figure 1: Illustration of the DFA-RIS architecture and the dynamic energy-saving design for DFA-RIS: A sub-array based DFA-RIS architecture.
  • Figure 2: Plane diagram of simulated sub-array based DFA-RIS assisted wireless communication system.
  • Figure 3: Energy efficiency versus the number of iterations.
  • Figure 4: Energy efficiency versus the maximum transmit power budget $P_{\max}^{BS}$.
  • Figure 5: The achievable sum-rate versus the maximum transmit power budget $P_{\max}^{BS}$.
  • ...and 3 more figures

Theorems & Definitions (1)

  • Theorem 1