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Pattern Division for Massive MIMO Networks with Two-stage Precoding

Research output: Contribution to journalArticle

Jianpeng Ma, Shun Zhang, Hongyan Li, Nan Zhao, Arumugam Nallanathan

Original languageEnglish
Pages (from-to)1665 - 1668
Publication statusPublished - 27 Mar 2017


  • Pattern Division for Massive_MA_Published27March2017_GREEN AAM (non-CC)

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    Accepted author manuscript


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King's Authors


In massive multiple-input multiple-output (MIMO) 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.

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