Alhabo, M, Zhang, L orcid.org/0000-0002-4535-3200 and Nawaz, N (2021) Handover for Dense Small Cells Heterogeneous Networks: A Power-efficient Game Theoretical Approach. International Journal of Electronics and Communication Engineering, 15 (5). pp. 194-199. ISSN 1307-6892
Abstract
In this paper, a non-cooperative game method is formulated where all players compete to transmit at higher power. Every base station represents a player in the game. The game is solved by obtaining the Nash equilibrium (NE) where the game converges to optimality. The proposed method, named Power Efficient Handover Game Theoretic (PEHO-GT) approach, aims to control the handover in dense small cell networks. Players optimize their payoff by adjusting the transmission power to improve the performance in terms of throughput, handover, power consumption and load balancing. To select the desired transmission power for a player, the payoff function considers the gain of increasing the transmission power. Then, the cell selection takes place by deploying Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS). A game theoretical method is implemented for heterogeneous networks to validate the improvement obtained. Results reveal that the proposed method gives a throughput improvement while reducing the power consumption and minimizing the frequent handover.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2021, World Academy of Science, Engineering and Technology. This is an open access article under the terms of the Creative Commons Attribution 4.0 International License. |
Keywords: | Energy efficiency, game theory, handover, HetNets, small cells |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Electronic & Electrical Engineering (Leeds) > Institute of Communication & Power Networks (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 09 Sep 2021 13:27 |
Last Modified: | 25 Jun 2023 22:44 |
Status: | Published |
Publisher: | World Academy of Science, Engineering and Technology (WASET) |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:177158 |