Open AccessGRA‐based handover for dense small cells heterogeneous networks
Author(s) -
Alhabo Mohanad,
Zhang Li,
Nawaz Naveed
Publication year - 2019
Publication title -
iet communications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.355
H-Index - 62
eISSN - 1751-8636
pISSN - 1751-8628
DOI - 10.1049/iet-com.2018.5938
Subject(s) - handover , computer science , heterogeneous network , weighting , analytic hierarchy process , quality of service , computer network , software deployment , grey relational analysis , cellular network , interference (communication) , vertical handover , service (business) , femtocell , process (computing) , distributed computing , wireless network , telecommunications , base station , operations research , wireless , channel (broadcasting) , medicine , mathematics , economy , mathematical economics , engineering , economics , radiology , operating system
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.