Multi-Criteria Handover Using Modified Weighted TOPSIS Methods for Heterogeneous Networks

Alhabo, Mohanad; Zhang, Li

doi:10.1109/access.2018.2846045

Cited by 62 publications

(75 citation statements)

References 18 publications

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“…The performance of the GRA-HO method is evaluated in terms of computational complexity, number of HOs, radio link failure and mean UE energy efficiency and compared against other two methods, the conventional SAW method and the conventional VIKOR method. Simulation parameters are listed in table 3 [22]. Distinguishing coefficient (Ψ) [9] 0.5…”

Section: Performance and Results Analysismentioning

confidence: 99%

GRA‐based handover for dense small cells heterogeneous networks

2019

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Ultra-dense small cell (SC) deployment in 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 (UE) will suffer from a degraded quality of service (QoS). In this paper, we propose a Grey Rational Analysis based handover method (GRA-HO) in dense SCs HetNet. The proposed method combines the Analytical Hierarchy Process (AHP) 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 (MADM) method including Simple Additive Weighting (SAW) 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 the energy efficiency.

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Section: Performance and Results Analysismentioning

confidence: 99%

GRA‐based handover for dense small cells heterogeneous networks

2019

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“…On the other hand, TOPSIS is also widely applied in the cell selection of HO as shown in papers [14]- [17]. The TOPSIS method is first developed by Hwang and Yoon [18].…”

Section: Related Workmentioning

confidence: 99%

“…The essential idea of TOPSIS is to seek for a candidate that with the shortest distance from the positive ideal solution (PIS) and with the farthest distance from negative ideal solution (NIS). Works in [14] proposed two novel TOPSIS-based HO algorithm in ultra-dense heterogeneous networks. The first algorithm adopts the entropy weighting technique to calculate weight value for each HO criteria.…”

Section: Related Workmentioning

confidence: 99%

Fuzzy-TOPSIS Based Optimal Handover Decision-making Algorithm for Fifth-generation of Mobile Communications System

Liu¹,

Kwong²,

Zhang³

et al. 2019

jcm

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With the increasing demand for higher bandwidth and data rate of the mobile user. There are massive base stations (BS) will be deployed in the future wireless environment. Several issues could be raised dues to dense deployment of BSs, i.e. handover (HO) ping-pong effect, unnecessary HO and frequent HO. To avoid these effects, the handover decision-making strategies become extremely important to select the optimal BS among all detected BS and ensure QoS for each mobile user. In this paper, the author develops a fuzzy-TOPSIS based HO algorithm to minimise the ping-pong effect and number of HO. The proposed algorithm integrates both advantages of fuzzy logic and TOPSIS. The received signal strength intensity (RSSI) and signal to noise ratio (SNR) are considered as HO criteria in this approach. For the simulation result, the proposed HO algorithm can reduce ping-pong rate and a number of HO effectivity by comparing to conventional RSSI-based HO approach and classical multi-attribute decision making (MADM) HO method, i.e. simple additive weighting (SAW) and TOPSIS.

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“…Then TOPSIS engine is implemented to select the best access networks amongst all candidates. Reference [20] proposed two novel TOPSIS-based handover algorithms in ultra-dense heterogeneous networks by using two different objective weighting approach entropy and standard deviation weighting techniques. These two weighting approaches can effectively avoid errors caused by human subjective decisions.…”

Section: Introductionmentioning

confidence: 99%

A fuzzy-clustering based approach for MADM handover in 5G ultra-dense networks

et al. 2019

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As the global data traffic has significantly increased in the recent year, the ultra-dense deployment of cellular networks (UDN) is being proposed as one of the key technologies in the fifthgeneration mobile communications system (5G) to provide a much higher density of radio resource. The densification of small base stations (BSs) could introduce much higher inter-cell interference and lead user to meet the edge of coverage more frequently. As the current handover scheme was originally proposed for macro BS, it could cause serious handover issues in UDN i.e. ping-pong handover, handover failures and frequent handover. In order to address these handover challenges and provide a high quality of service (QoS) to the user in UDN. This paper proposed a novel handover scheme, which integrates both advantages of fuzzy logic and multiple attributes decision algorithms (MADM) to ensure handover process be triggered at the right time and connection be switched to the optimal neighbouring BS. To further enhance the performance of the proposed scheme, this paper also adopts the subtractive clustering technique by using historical data to define the optimal membership functions within the fuzzy system.Performance results show that the proposed handover scheme outperforms traditional approaches and can significantly minimise the number of handovers and the ping-pong handover while maintaining QoS at a relatively high level.

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Multi-Criteria Handover Using Modified Weighted TOPSIS Methods for Heterogeneous Networks

Cited by 62 publications

References 18 publications

GRA‐based handover for dense small cells heterogeneous networks

GRA‐based handover for dense small cells heterogeneous networks

Fuzzy-TOPSIS Based Optimal Handover Decision-making Algorithm for Fifth-generation of Mobile Communications System

A fuzzy-clustering based approach for MADM handover in 5G ultra-dense networks

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