LAPSE:2018.0894
Published Article
LAPSE:2018.0894
A Biologically-Inspired Power Control Algorithm for Energy-Efficient Cellular Networks
November 27, 2018
Most of the energy used to operate a cellular network is consumed by a base station (BS), and reducing the transmission power of a BS can therefore afford a substantial reduction in the amount of energy used in a network. In this paper, we propose a distributed transmit power control (TPC) algorithm inspired by bird flocking behavior as a means of improving the energy efficiency of a cellular network. Just as each bird in a flock attempts to match its velocity with the average velocity of adjacent birds, in the proposed algorithm, each mobile station (MS) in a cell matches its rate with the average rate of the co-channel MSs in adjacent cells by controlling the transmit power of its serving BS. We verify that this bio-inspired TPC algorithm using a local rate-average process achieves an exponential convergence and maximizes the minimum rate of the MSs concerned. Simulation results show that the proposed TPC algorithm follows the same convergence properties as the flocking algorithm and also effectively reduces the power consumption at the BSs while maintaining a low outage probability as the inter-cell interference increases; in so doing, it significantly improves the energy efficiency of a cellular network.
Keywords
bio-inspired algorithm, Energy Efficiency, energy-efficient cellular network, flocking model, green base station, power control algorithm
Suggested Citation
Choi HH, Lee JR. A Biologically-Inspired Power Control Algorithm for Energy-Efficient Cellular Networks. (2018). LAPSE:2018.0894
Author Affiliations
Choi HH: Department of Electrical, Electronic and Control Engineering, Institute for Information Technology Convergence, Hankyong National University, 327 Chungang-ro, Anseong 17579, Korea [ORCID]
Lee JR: School of the Electrical Engineering, Chung-Ang University, 84 Heukseok-ro, Dongjak-gu, Seoul 06974, Korea [ORCID]
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Journal Name
Energies
Volume
9
Issue
3
Article Number
E161
Year
2016
Publication Date
2016-03-04
Published Version
ISSN
1996-1073
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PII: en9030161, Publication Type: Journal Article
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LAPSE:2018.0894
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doi:10.3390/en9030161
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Nov 27, 2018
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CC BY 4.0
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Nov 27, 2018
 
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Original Submitter
Calvin Tsay
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