Graph Based User Clustering for HAP Massive MIMO Systems With Two-stage Beamforming

被引：1

作者：

Ji, Pingping ^{[1
]}

Jiang, Lingge ^{[1
]}

He, Chen ^{[1
]}

He, Di ^{[1
]}

机构：

[1] Shanghai Jiao Tong Univ, Dept Elect Engn, Shanghai, Peoples R China

来源：

2019 22ND INTERNATIONAL SYMPOSIUM ON WIRELESS PERSONAL MULTIMEDIA COMMUNICATIONS (WPMC) | 2019年

基金：

中国国家自然科学基金;

关键词：

User clustering; maximal clique; Bron-Kerbosch; high altitude platform; massive MIMO; two-stage beamforming; TRANSMISSION; DOWNLINK; CLIQUES;

D O I：

10.1109/wpmc48795.2019.9096130

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

We propose a user clustering algorithm based on graph theory with two-stage beamforming for high-altitude platform (HAP) massive multiple-input multiple-output (MIMO) systems. First, we construct a conflict graph, where each vertex is the user and each edge is measured by the similarity of correlation matrix distance (CMD) between users. Then, in the aim of alleviating the self-cluster interference (SCI), a novel low-complexiy user clustering method is introduced, where the algorithm is Bron-Kerbosch to enumerate all the maximal cliques, and maximal clusters are obtained by the cluster formation algorithm. As shown in the numerical results, the performance of the proposed algorithm has a significant increase.

引用

页数：6

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