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A reinforcement learning based algorithm towards energy efficient 5G multi-tier network

conference contribution
posted on 05.11.2019, 00:00 by Nahina Islam, A Alazab, M Alazab
Energy efficiency is a key factor in the next generation wireless communication systems. Sleep mode implementation in multi-tier 5G networks has proven to be a very good approach for improving the energy efficiency. In this paper we have proposed a novel reinforcement learning based decision making algorithm to implement sleep mode in the base stations (BSs) used in multi-tier 5G networks. we have pro- posed a Markovian Decision process (MDP) based algorithm to switch between three different power consumption modes of a BS for improving the energy efficiency of the 5G network. The MDP based approach intelligently switches between the states of the BS based on the offered traffic whilst maintaining a prescribed minimum channel rate per user. Our results show that there is a signi ficant gain in the energy efficiency when using our proposed MDP algorithm together with the three-state BSs. We have also shown the energy-delay trade-off in order to design a delay aware network.

History

Start Page

96

End Page

101

Number of Pages

6

Start Date

07/05/2019

Finish Date

08/05/2019

ISBN-13

9781728126005

Location

Melbourne, Australia

Publisher

IEEE

Place of Publication

Piscataway, NJ

Peer Reviewed

Yes

Open Access

No

External Author Affiliations

Melbourne Institute of Technology; Charles Darwin University

Era Eligible

Yes

Name of Conference

Cybersecurity and Cyberforensics Conference (CCC)

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