inis 23(4):

Research Article

Jointly power allocation and phase shift optimization for RIS empowered downlink cellular networks

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  • @ARTICLE{10.4108/eetinis.v10i4.4359,
        author={Phuc Quang Truong and Tan Do-Duy and Van-Ca Phan and Antonino Masaracchia},
        title={Jointly power allocation and phase shift optimization for RIS empowered downlink cellular networks},
        journal={EAI Endorsed Transactions on Industrial Networks and Intelligent Systems},
        volume={10},
        number={4},
        publisher={EAI},
        journal_a={INIS},
        year={2023},
        month={12},
        keywords={6G, Optimization, Phase-Shaft Optimization, QoS, Resource Allocation, RIS, Throughput Maximization},
        doi={10.4108/eetinis.v10i4.4359}
    }
    
  • Phuc Quang Truong
    Tan Do-Duy
    Van-Ca Phan
    Antonino Masaracchia
    Year: 2023
    Jointly power allocation and phase shift optimization for RIS empowered downlink cellular networks
    INIS
    EAI
    DOI: 10.4108/eetinis.v10i4.4359
Phuc Quang Truong1, Tan Do-Duy1, Van-Ca Phan1, Antonino Masaracchia2,*
  • 1: Ho Chi Minh City University of Technology
  • 2: Queen's University Belfast
*Contact email: antonino.masaracchia@gmail.com

Abstract

Reconfigurable Intelligent Surfaces (RIS) have been highlighted by the research community as a key enabling technology for the enhancement of next-generation wireless network performance, including energy efficiency, spectral efficiency, and network throughput. This paper investigates how RIS-assisted communication can effectively maximize the downlink throughput of a cellular network. Specifically, the paper considers a communication scenario where a single base station serves multiple ground users with the aid of an RIS placed on a building facade. For such a communication scenario, we considered an optimization problem aimed at maximizing the overall downlink throughput by jointly optimizing power allocation at the base station and phase shift of RIS reflecting elements, subject to power consumption and quality-of-service constraints. To address its non-convex nature, the original optimization problem has been divided into two subproblems. The first one, for power control with fixed phase shift values, is a convex problem that can be easily solved. Subsequently, a phase shift searching procedure to solve the non-convex problem of RIS phase shift optimization has been adopted. The results from numerical simulations show that the proposed method outperforms other conventional methods proposed in the literature. In addition, computational complexity analysis has been conducted to prove the low complexity of the proposed method.