Joint Power Control and Passive Beamforming in Reconfigurable Intelligent Surface Assisted User-Centric Networks

被引:8
作者
Lu, Hancheng [1 ,2 ]
Zhao, Dan [1 ]
Wang, Yazheng [1 ]
Kong, Chani [1 ]
Chen, Weidong [3 ]
机构
[1] Univ Sci & Technol China, CAS Key Lab Wireless Opt Commun, Hefei 230027, Peoples R China
[2] Hefei Comprehens Natl Sci Ctr, Inst Artificial Intelligence, Hefei 230027, Peoples R China
[3] Univ Sci & Technol China, Sch Informat Sci & Technol, Hefei 230027, Peoples R China
基金
美国国家科学基金会; 国家重点研发计划;
关键词
Power control; Interference; Power demand; Optimization; Downlink; Costs; Computer architecture; Reconfigurable intelligent surface; user-centric network; passive beamforming; power control; energy efficiency; ULTRA-DENSE NETWORKS; REFLECTING SURFACE; CHANNEL ESTIMATION; MASSIVE MIMO; CELL-FREE; ENERGY EFFICIENCY; WIRELESS NETWORK; OPTIMIZATION; ALLOCATION; FRAMEWORK;
D O I
10.1109/TCOMM.2022.3174071
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
As a promising technology with disruptive innovation, user-centric network can meet the data traffic demand and user service demand in the future mobile networks. It completely transforms the traditional cell-centric paradigm into user-centric paradigm, requiring the deployment of a large number of access points (APs). However, the massive deployment of APs leads to issues such as high hardware cost, huge power consumption and complex interference management. Reconfigurable intelligent surfaces (RIS), as another promising technology, can expand signal coverage, suppress interference, reduce hardware cost and power consumption. Inspired by this, we propose a novel RIS assisted user-centric network that uses RIS to replace some low utilization APs to reduce cost as well as power consumption, and deploy more RIS to achieve energy-efficient user-centric communication. In order to take full advantages of RIS, we jointly optimize passive beamforming at RIS and power control at AP to maximize the energy efficiency of the network. Since this problem is intractable and non-convex, an effectively alternating optimization algorithm, capitalizing on fractional programming and successive lower-bound maximization is proposed. The simulation results verify that the proposed algorithm outperforms reference algorithms in terms of energy efficiency and sum rate.
引用
收藏
页码:4852 / 4866
页数:15
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