Reconfigurable Intelligent Surfaces Aided Energy Efficiency Maximization in Cell-Free Networks

被引:1
作者
Wang, Kewei [1 ,2 ]
Qi, Nan [1 ,2 ]
Liu, Haoxuan [1 ]
Boulogeorgos, Alexandros-Apostolos A. [3 ]
Tsiftsis, Theodoros A. [4 ]
Xiao, Ming [5 ]
Wong, Kai-Kit [6 ]
机构
[1] Nanjing Univ Aeronaut & Astronaut, Key Lab Dynam Cognit Syst Electromagnet Spectrum S, Nanjing 210016, Peoples R China
[2] Xidian Univ, State Key Lab Integrated Serv Networks, Xian 710071, Peoples R China
[3] Univ Western Macedonia, Dept Elect & Comp Engn, Kozani 50100, Greece
[4] Univ Thessaly, Dept Informat & Telecommun, Lamia 35100, Greece
[5] KTH Royal Inst Technol, Sch Elect Engn, S-10044 Stockholm, Sweden
[6] UCL, Dept Elect & Elect Engn, London WC1E 7JE, England
基金
中国国家自然科学基金;
关键词
Array signal processing; Optimization; Vectors; Transforms; Power demand; Signal to noise ratio; Reconfigurable intelligent surface; cell-free network; energy efficiency maximization; fractional programming; beamforming;
D O I
10.1109/LWC.2024.3382778
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
As we move towards next-generation wireless networks, the need for sustainability through energy efficiency (EE) concepts becomes more important than ever. Meanwhile, technology enablers, such as beamforming and reconfigurable intelligent surfaces (RISs), if appropriately used in a synergetic manner, can deliver profound excellence in terms of EE. Motivated by this, in this letter, we introduce an EE maximization policy that accounts for the rate demands of the end-users in RIS-assisted cell-free networks. The policy aims at performing joint optimization of the transmit beamforming vectors and the RIS phase-shift matrices in order to maximize the EE. In this direction, we first formulate the corresponding optimization problem, which is non-convex. To solve it, we rely on advanced optimization methods such as quadratic and Lagrangian dual transforms. Numerical results highlight the superiority of the presented policy in comparison to baseline approaches and reveal the most impactful network parameters.
引用
收藏
页码:1596 / 1600
页数:5
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