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Reinforcement Learning for Delay-Constrained Energy-Aware Small Cells with Multi-Sleeping Control

Authors: Ali El-Amine; Paolo Dini; Loutfi Nuaymi;

Reinforcement Learning for Delay-Constrained Energy-Aware Small Cells with Multi-Sleeping Control

Abstract

In 5G networks, specific requirements are defined on the periodicity of Synchronization Signaling (SS) bursts. This imposes a constraint on the maximum period a Base Station (BS) can be deactivated. On the other hand, BS densification is expected in 5G architecture. This will cause a drastic increase in the network energy consumption followed by a complex interference management. In this paper, we study the Energy-Delay-Tradeoff (EDT) problem in a Heterogeneous Network (HetNet) where small cells can switch to different sleep mode levels to save energy while maintaining a good Quality of Service (QoS). We propose a distributed Q-learning algorithm controller for small cells that adapts the cell activity while taking into account the co-channel interference between the cells. Our numerical results show that multi-level sleep scheme outperforms binary sleep scheme with an energy saving up to 80% in the case when the users are delay tolerant, and while respecting the periodicity of the SS bursts in 5G.

Country
France
Keywords

[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI], multi-level sleep mode, delay, Energy saving, Q-learning, [INFO.INFO-LG] Computer Science [cs]/Machine Learning [cs.LG], 5G, [SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing, [SPI.NRJ] Engineering Sciences [physics]/Electric power, delay,

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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