Alhabo, M, Zhang, L and Nawaz, N (2019) GRA-based Handover for Dense Small Cells Heterogeneous Networks. IET Communications, 13 (13). pp. 1928-1935. ISSN 1751-8628
Abstract
Ultra-dense small cell (SC) deployment in the future 5G network makes the architecture of the network as heterogeneous networks (HetNets). This is a good solution to boost the capacity of the network and extend its coverage. However, the dense SCs deployment has brought new challenges to the network including interference, frequent unnecessary handovers, and handover failures. Therefore, user equipment will suffer from a degraded quality of service. In this paper, the authors propose a grey rational analysis-based handover (GRA-HO) method in dense SCs HetNet. The proposed method combines the analytical hierarchy process technique to obtain the weight of the handover metrics and the GRA method to rank the available cells for the best handover target. The performance of the proposed method is evaluated and compared with the traditional multiple attribute decision-making methods including simple additive weighting and VIKOR methods. Results show that the GRA-HO method has outperformed the existing methods in terms of reducing the number of frequent handovers and link failures, in addition to enhancing energy efficiency.
Metadata
Item Type: | Article |
---|---|
Authors/Creators: |
|
Copyright, Publisher and Additional Information: | © The Institution of Engineering and Technology. This paper is a postprint of a paper submitted to and accepted for publication in IET Communications and is subject to Institution of Engineering and Technology Copyright. The copy of record is available at the IET Digital Library. |
Keywords: | fuzzy set theory; mobility management (mobile radio); decision making; grey systems; quality of service |
Dates: |
|
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: | 18 Jul 2019 10:44 |
Last Modified: | 01 Aug 2019 22:59 |
Status: | Published |
Publisher: | Institution of Engineering and Technology |
Identification Number: | 10.1049/iet-com.2018.5938 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:148693 |