Open Access

ARTICLE

Conflict Resolution Strategy in Handover Management for 4G and 5G Networks

by Abdulraqeb Alhammadi^1,*, Wan Haslina Hassan¹, Ayman A. El-Saleh², Ibraheem Shayea³, Hafizal Mohamad⁴, Yousef Ibrahim Daradkeh⁵

1 Communication Systems and Networks Research Lab, Malaysia-Japan International Institute of Technology, Universiti Teknologi Malaysia, 54100, Kuala Lumpur, Malaysia
2 College of Engineering, A'sharqiyah University (ASU), Ibra, 400, Oman
3 Department of Electronics and Communication Engineering, Faculty of Electrical and Electronics Engineering, Istanbul Technical University (ITU), Istanbul, 34467, Turke
4 Faculty of Engineering and Built Environment, Universiti Sains Islam Malaysia, Bandar Baru Nilai, 71800, Malaysia
5 Department of Computer Engineering and Networks, College of Engineering at Wadi Addawasir, Prince Sattam Bin Abdulaziz University, Al Kharj, 11991, KSA

* Corresponding Author: Abdulraqeb Alhammadi. Email:

Computers, Materials & Continua 2022, 72(3), 5215-5232. https://doi.org/10.32604/cmc.2022.024713

Received 28 October 2021; Accepted 03 December 2021; Issue published 21 April 2022

Abstract

Fifth-generation (5G) cellular networks offer high transmission rates in dense urban environments. However, a massive deployment of small cells will be required to provide wide-area coverage, which leads to an increase in the number of handovers (HOs). Mobility management is an important issue that requires considerable attention in heterogeneous networks, where 5G ultra-dense small cells coexist with current fourth-generation (4G) networks. Although mobility robustness optimization (MRO) and load balancing optimization (LBO) functions have been introduced in the 3GPP standard to address HO problems, non-robust and nonoptimal algorithms for selecting appropriate HO control parameters (HCPs) still exist, and an optimal solution is subjected to compromise between LBO and MRO functions. Thus, HO decision algorithms become inefficient. This paper proposes a conflict resolution technique to address the contradiction between MRO and LBO functions. The proposed technique exploits received signal reference power (RSRP), cell load and user speed to adapt HO margin (HM) and time to trigger (TTT). Estimated HM and TTT depend on a weighting function and HO type which is represented by user status during mobility. The proposed technique is validated with other existing algorithms from the literature. Simulation results demonstrate that the proposed technique outperforms existing algorithms overall performance metrics. The proposed technique reduces the overall average HO ping-pong probability, HO failure rate and interruption time by more than 90%, 46% and 58%, respectively, compared with the other schemes overall speed scenarios and simulation time.

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Keywords

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