Pattern Division for Massive MIMO Networks With Two-Stage Precoding

被引：11
|
作者：
Ma, Jianpeng [1 ]
Zhang, Shun [1 ]
Li, Hongyan [1 ]
Zhao, Nan [2 ]
Nallanathan, Arumugam [3 ]
机构：
[1] Xidian Univ, State Key Lab Integrated Serv Networks, Xian 710071, Peoples R China
[2] Dalian Univ Technol, Sch Informat & Commun Engn, Dalian 116024, Peoples R China
[3] Kings Coll London, Dept Informat, London WC2R 2LS, England
来源：
IEEE COMMUNICATIONS LETTERS | 2017年 / 21卷 / 07期
基金：
英国工程与自然科学研究理事会; 美国国家科学基金会;
关键词：
Graph theory; massive MIMO; pattern division; two-stage precoding;
D O I：
10.1109/LCOMM.2017.2687868
中图分类号：
TN [电子技术、通信技术];
学科分类号：
0809 ;
摘要：
In massive multiple-input multiple-output networks with two-stage precoding, the user clusters with serious angle-spreading-range (ASR) overlapping should be divided into different patterns and scheduled in orthogonal sub-channels to achieve optimal performance. In this letter, we propose one graph theory-based pattern division (GT-PD) scheme to deal with the ASR overlapping with a limited number of sub-channels. First, we depict the ASR overlapping as an undirected weighted graph, where the weight of each edge indicates the strength of the ASR overlapping between two connected clusters. Then, we separately denote each user cluster and pattern as a vertex and a color, and transform the pattern division into a graph coloring problem with limited colors. In addition, the GT-PD scheme is developed with the help of the Dsatur algorithm. Finally, numerical results are provided to corroborate the efficiency of the proposed scheme.
引用
收藏
页码：1665 / 1668
页数：4
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