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Energy Efficiency Optimization for Hybrid Active-Passive RIS Aided Communications: A Novel Dynamic Subarray-Based Architecture
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DOI：10.1109/TWC.2025.3636588.png)
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Abstract
En 中文
Reconfigurable intelligent surface (RIS) has emerged as a promising technology for greatly enhancing communication performance of future wireless networks. To overcome the multiplicative fading effect of passive RIS and high energy consumption of active RIS, we propose a novel dynamic subarray-based hybrid active-passive RIS (HRIS) architecture by dividing all reflecting elements into multiple sub-RISs, each of which can flexibly switch between active and passive modes. Therefore, the proposed subarray-based HRIS is anticipated to achieve optimal system performance with minimal cost and energy consumption. In this paper, we aim to maximize the energy efficiency (EE) for the subarray-based HRIS assisted multi-user multiple-input single-output (MISO) system, where the transmit beamforming vectors at the base station (BS), the mode switching matrix, and the reflection matrices of active and passive sub-RISs are jointly optimized subject to individual user rate constraints. To tackle this intractable problem, we firstly explore the feasible region of the minimum rate threshold among all users, and then develop an efficient two-layer successive convex approximation (SCA) based iterative algorithm. Considering a simplified single-user scenario, we also derive some interesting insights into the optimal active-passive sub-RISs allocation for maximizing EE. It is revealed that for a small BS transmit power, deploying more active sub-RISs in the subarray-based HRIS is preferred to attain the maximum EE. Conversely, under a high BS transmit power and a small HRIS reflection power, more sub-RISs should be switched to the passive mode. Numerical simulation results verify the superior EE performance of the proposed dynamic subarray-based HRIS over the traditional active and passive RISs.
Keywords:
Reconfigurable intelligent surface
dynamic active-passive sub-RISs allocation
energy efficiency maximization
beamforming design
Journal
IF:
10.7
Papers:
1.3W
Citations:
5.3W
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