A Q-Learning-Based Downlink Power Control Algorithm for Energy Efficiency in LTE Femtocells

Femtocell is introduced to improve indoor coverage, which is beneficial for both users and operators. But it will also inevitably produce interference management issues in the heterogeneous network which consists of femtocells and macrocells. In this paper, a decentralized Q-learning-based power con...

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Bibliographic Details
Published inApplied Mechanics and Materials Vol. 556-562; pp. 1766 - 1769
Main Authors Huang, Lian Fen, Li, Yu Jie, Gao, Zhi Bin, Cai, Hong Xiang, Wen, Bin
Format Journal Article
LanguageEnglish
Published Zurich Trans Tech Publications Ltd 01.05.2014
Subjects
Q-Learning
Power Control
Heterogeneous Network
LTE
Energy Efficiency
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Summary:Femtocell is introduced to improve indoor coverage, which is beneficial for both users and operators. But it will also inevitably produce interference management issues in the heterogeneous network which consists of femtocells and macrocells. In this paper, a decentralized Q-learning-based power control strategy is proposed, comparing with homogenous power allocation and smart power control (SPC) algorithm. Simulation results have shown that Q-learning-based power control algorithm can implement the compromise of capacity between macrocells and femtocells, and greatly enhance energy efficiency of the whole network.
Bibliography:Selected, peer reviewed papers from the 2014 International Conference on Mechatronics Engineering and Computing Technology (ICMECT 2014), April 9-10, 2014, Shanghai, China
ISBN:3038351156
9783038351153
ISSN:1660-9336
1662-7482
1662-7482
DOI:10.4028/www.scientific.net/AMM.556-562.1766