Joint Power Allocation in Interference-Limited Networks via Distributed Coordinated Learning

被引：0

作者：

Amiri, Roohollah ^{[1
]}

Mehrpouyan, Hani ^{[1
]}

Matolak, David ^{[2
]}

Elkashlan, Maged ^{[3
]}

机构：

[1] Boise State Univ, Sch Elect & Comp Engn, Boise, ID 83725 USA

[2] Univ South Carolina, Dept Elect Engn, Columbia, SC USA

[3] Queen Mary Univ London, Sch Elect Engn & Comp Sci, London, England

来源：

2018 IEEE 88TH VEHICULAR TECHNOLOGY CONFERENCE (VTC-FALL) | 2018年

关键词：

D O I：

暂无

中图分类号：

U [交通运输];

学科分类号：

08 ; 0823 ;

摘要：

Dense deployment of small base stations (SBSs) is one of the main methods to meet the 5G data rate requirements. However, high density of independent SBSs will increase the interference within the network. To circumvent this interference, there is a need to develop self-organizing methods to manage the resources of the network. In this paper, we present a distributed power allocation algorithm based on multi-agent Q-learning in an interference-limited network. The proposed method leverages coordination through simple message passing between SBSs to achieve an optimal joint power allocation. Simulation results show the optimality of the proposed method for a two-user case.

引用

页数：5

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