Beamforming for heterogeneous cloud radio access network

被引：0
|
作者：
Zuo J. [1 ,2 ]
Yang L. [2 ]
Bao N. [1 ]
机构：
[1] College of Internet of Things, Nanjing University of Posts and Telecommunications, Nanjing
[2] College of Telecommunications and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing
来源：
Tongxin Xuebao/Journal on Communications | 2019年 / 40卷 / 08期
基金：
中国国家自然科学基金;
关键词：
Alternating optimization; Beamforming; Key words: heterogeneous cloud radio access network; Multi-antenna technology;
D O I：
10.11959/j.issn.1000-436x.2019170
中图分类号：
学科分类号：
摘要：
To overcome the problem that previous researches for heterogeneous cloud radio access network (H-CRAN) mainly focus on single macro cell, and only considered the intracell interference in the one macro cell, while the inter cell interferences among different macro cells are neglected, H-CRAN with multiple macro-cells was studied, and the objective was to maximize system sum-rate through jointly optimizing the beamforming vectors of macro base stations (MBS) and remote radio heads (RRH). Based on alternating optimization and Lagrangian dual method, a joint MBS and RRH beamforming algorithm was proposed. The original problem was first divided into two subproblems. Then, the two sub-problem were solved alternately to obtain the final solutions of the original problem. In addition, the closed expression solutions of the two sub-problem were derived based on Lagrangian dual method. The proposed algorithm was compared with some beamforming algorithms in the simulation. The experimental results demonstrate the proposed algorithm has a better performance in improving the sum-rate of H-CRAN. © 2019, Editorial Board of Journal on Communications. All right reserved.
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页码：45 / 53
页数：8
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