Directed-Hypergraph-Based Channel Allocation for Ultradense Cloud D2D Communications With Asymmetric Interference

被引：16

作者：

Sun, Youming ^{[1
]}

Du, Zhiyong ^{[2
]}

Xu, Yuhua ^{[1
]}

Zhang, Yuli ^{[1
]}

Jia, Luliang ^{[1
]}

Anpalagan, Alagan ^{[3
]}

机构：

[1] Army Engn Univ, Nanjing 210000, Jiangsu, Peoples R China

[2] Natl Univ Def Technol, Changsha 410000, Hunan, Peoples R China

[3] Ryerson Univ, Dept Elect & Comp Engn, Toronto, ON M5B 2K3, Canada

来源：

IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY | 2018年 / 67卷 / 08期

关键词：

Directed hypergraph; Channel allocation; Device-to-device communications; Exact potential game; Learning algorithm; NETWORKS;

D O I：

10.1109/TVT.2018.2839352

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：

In this paper, we investigate channel allocation for ultradense device-to-device (D2D) communications. Different from both binary graph and undirected hypergraph interference model, an improved directed hypergraph is applied to simultaneously represent cumulative and asymmetric interference aspects in the context of ultradense communications. We formulate the channel access problem in cloud D2D communication networks as a directed-hypergraph-based local altruistic game, which is proved to be an exact potential game. Then, a multiagent concurrent learning scheme in centralized-distributed fashion is proposed to search the optimal pure Nash equilibrium, which can also maximize the normalized network capacity. Finally, simulation results are presented to validate the proposed learning scheme.

引用

页码：7712 / 7718

页数：7

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