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Memory-full Context-aware Predictive Mobility Management in Dual Connectivity 5G Networks

Mohamed, Abdelrahim, Imran, Muhammad, Xiao, Pei and Tafazolli, Rahim (2018) Memory-full Context-aware Predictive Mobility Management in Dual Connectivity 5G Networks IEEE Access, 6. pp. 9655-9666.

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Network densification with small cell deployment is being considered as one of the dominant themes in the fifth generation (5G) cellular system. Despite the capacity gains, such deployment scenarios raise several challenges from mobility management perspective. The small cell size, which implies a small cell residence time, will increase the handover (HO) rate dramatically. Consequently, the HO latency will become a critical consideration in the 5G era. The latter requires an intelligent, fast and light-weight HO procedure with minimal signalling overhead. In this direction, we propose a memory-full context-aware HO scheme with mobility prediction to achieve the aforementioned objectives. We consider a dual connectivity radio access network architecture with logical separation between control and data planes because it offers relaxed constraints in implementing the predictive approaches. The proposed scheme predicts future HO events along with the expected HO time by combining radio frequency performance to physical proximity along with the user context in terms of speed, direction and HO history. To minimise the processing and the storage requirements whilst improving the prediction performance, a user-specific prediction triggering threshold is proposed. The prediction outcome is utilised to perform advance HO signalling whilst suspending the periodic transmission of measurement reports. Analytical and simulation results show that the proposed scheme provides promising gains over the conventional approach.

Item Type: Article
Divisions : Faculty of Engineering and Physical Sciences > Electronic Engineering
Authors :
Date : 23 January 2018
Funders : Engineering and Physical Sciences Research Council (EPSRC)
DOI : 10.1109/ACCESS.2018.2796579
Grant Title : EPSRC Global Challenges Research Fund through the DARE Project
Copyright Disclaimer : © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.
Uncontrolled Keywords : Context awareness; Control/data separation architecture; Memory-full networking; Mobility management
Depositing User : Clive Harris
Date Deposited : 23 Jan 2018 11:24
Last Modified : 11 Dec 2018 11:23

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