Reconfigurable Intelligent Surfaces for Energy Efficiency in Wireless Communication
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In this article, the authors developed energy-efficient designs for both the transmit power allocation and the phase shifts of the surface reflecting elements subject to individual link budget guarantees for the mobile users.Abstract:
The adoption of a reconfigurable intelligent surface (RIS) for downlink multi-user communication from a multi-antenna base station is investigated in this paper. We develop energy-efficient designs for both the transmit power allocation and the phase shifts of the surface reflecting elements subject to individual link budget guarantees for the mobile users. This leads to non-convex design optimization problems for which to tackle we propose two computationally affordable approaches, capitalizing on alternating maximization, gradient descent search, and sequential fractional programming. Specifically, one algorithm employs gradient descent for obtaining the RIS phase coefficients, and fractional programming for optimal transmit power allocation. Instead, the second algorithm employs sequential fractional programming for the optimization of the RIS phase shifts. In addition, a realistic power consumption model for RIS-based systems is presented, and the performance of the proposed methods is analyzed in a realistic outdoor environment. In particular, our results show that the proposed RIS-based resource allocation methods are able to provide up to 300% higher energy efficiency in comparison with the use of regular multi-antenna amplify-and-forward relaying.read more
Citations
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Journal ArticleDOI
Reconfigurable Intelligent Surface Enabled Full-Duplex/Half-Duplex Cooperative Non-Orthogonal Multiple Access
TL;DR: In this article , the authors investigated the downlink transmission of reconfigurable intelligent surface (RIS)-aided cooperative non-orthogonal-multiple access (C-NOMA) networks, where both HD and FD relaying modes were considered.
Journal ArticleDOI
AI Empowered RIS-Assisted NOMA Networks: Deep Learning or Reinforcement Learning?
TL;DR: In this paper , a reconfigurable intelligent surface (RIS)-assisted multi-user downlink communication system over fading channels is investigated, where both NOMA and orthogonal multiple access (OMA) schemes are employed.
Posted Content
Design and Evaluation of Reconfigurable Intelligent Surfaces in Real-World Environment.
Georgios C. Trichopoulos,Panagiotis C. Theofanopoulos,Bharath G. Kashyap,Aditya Shekhawat,Anuj Y. Modi,Tawfik Osman,Sanjay Kumar,Anand Sengar,Arkajyoti Chang,Ahmed Alkhateeb +9 more
TL;DR: In this article, the authors developed an RIS proof-of-concept prototype and extensively evaluated its potential gains in the field and under realistic wireless communication settings, where a 160-element reconfigurable surface, operating at a 5.8GHz band, is first designed, fabricated, and accurately measured in the anechoic chamber.
Journal ArticleDOI
Reconfigurable Intelligent Surface-Assisted Multi-UAV Networks: Efficient Resource Allocation With Deep Reinforcement Learning
TL;DR: In this article , a deep reinforcement learning (DRLRL) approach is proposed for solving the continuous optimisation problem with time-varying channels in a centralised fashion, and parallel learning approach is also proposed for reducing the latency of information transmission requirement of the centralised approach.
Posted Content
Study of Intelligent Reflective Surface Assisted Communications with One-bit Phase Adjustments
TL;DR: This work analyses the performance of a communication link assisted by an intelligent reflective surface (IRS) positioned in the far field of both the source and the destination and obtains the diversity orders for systems with and without phase errors.
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