Sum Rate Maximization Under AoI Constraints for RIS-Assisted mmWave Communications

被引:0
|
作者
Guo, Ziqi [1 ,2 ]
Niu, Yong [1 ]
Mao, Shiwen [3 ]
Zhang, Changming [4 ]
Wang, Ning [5 ]
Zhong, Zhangdui [1 ,6 ]
Ai, Bo [1 ,6 ]
机构
[1] Beijing Jiaotong Univ, State Key Lab Adv Rail Autonomous Operat, Beijing 100044, Peoples R China
[2] Beijing Jiaotong Univ, Collaborat Innovat Ctr Railway Traff Safety, Beijing 100044, Peoples R China
[3] Auburn Univ, Dept Elect & Comp Engn, Auburn, AL 36849 USA
[4] Zhejiang Lab, Res Inst Intelligent Networks, Hangzhou 311121, Peoples R China
[5] Zhengzhou Univ, Sch Informat Engn, Zhengzhou 450001, Peoples R China
[6] Beijing Jiaotong Univ, Beijing Engn Res Ctr High speed Railway Broadband, Beijing 100044, Peoples R China
关键词
Reconfigurable intelligent surface (RIS); age of information (AoI); beamforming; discrete phase shifts; scheduling; INTELLIGENT REFLECTING SURFACE; WIRELESS NETWORKS; OPTIMIZING AGE; INFORMATION; DESIGN;
D O I
10.1109/TVT.2023.3331707
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
The concept of age of information (AoI) has been proposed to quantify information freshness, which is crucial for time-sensitive applications. However, in millimeter wave (mmWave) communication systems, the link blockage caused by obstacles and the severe path loss greatly impair the freshness of information received by the user equipments (UEs). In this article, we focus on reconfigurable intelligent surface (RIS)-assisted mmWave communications, where beamforming is performed at transceivers to provide directional beam gain and a RIS is deployed to combat link blockage. We aim to maximize the system sum rate while satisfying the information freshness requirements of UEs by jointly optimizing the beamforming at transceivers, the discrete RIS reflection coefficients, and the UE scheduling strategy. To facilitate a practical solution, we decompose the problem into two subproblems. For the first per-UE data rate maximization problem, we further decompose it into a beamforming optimization subproblem and a RIS reflection coefficient optimization subproblem. Considering the difficulty of channel estimation, we utilize the hierarchical search method for the former and the local search method for the latter, and then adopt the block coordinate descent (BCD) method to alternately solve them. For the second scheduling strategy design problem, a low-complexity heuristic scheduling algorithm is designed. Simulation results show that the proposed algorithm can effectively improve the system sum rate while satisfying the information freshness requirements of all UEs.
引用
收藏
页码:5243 / 5258
页数:16
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