Handover parameters optimisation techniques in 5g networks

Wasan Kadhim Saad*, Ibraheem Shayea, Bashar J. Hamza, Hafizal Mohamad, Yousef Ibrahim Daradkeh, Waheb A. Jabbar

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    38 Citations (SciVal)

    Abstract

    The massive growth of mobile users will spread to significant numbers of small cells for the Fifth Generation (5G) mobile network, which will overlap the fourth generation (4G) network. A tremendous increase in handover (HO) scenarios and HO rates will occur. Ensuring stable and reliable connection through the mobility of user equipment (UE) will become a major problem in future mobile networks. This problem will be magnified with the use of suboptimal handover control parameter (HCP) settings, which can be configured manually or automatically. Therefore, the aim of this study is to investigate the impact of different HCP settings on the performance of 5G network. Several system scenarios are proposed and investigated based on different HCP settings and mobile speed scenarios. The different mobile speeds are expected to demonstrate the influence of many proposed system scenarios on 5G network execution. We conducted simulations utilizing MATLAB software and its related tools. Evaluation comparisons were performed in terms of handover probability (HOP), ping-pong handover probability (PPHP) and outage probability (OP). The 5G network framework has been employed to evaluate the proposed system scenarios used. The simulation results reveal that there is a trade-off in the results obtained from various systems. The use of lower HCP settings provides noticeable enhancements compared to higher HCP settings in terms of OP. Simultaneously, the use of lower HCP settings provides noticeable drawbacks compared to higher HCP settings in terms of high PPHP for all scenarios of mobile speed. The simulation results show that medium HCP settings may be the acceptable solution if one of these systems is applied. This study emphasises the application of automatic self-optimisation (ASO) functions as the best solution that considers user experience.
    Original languageEnglish
    Article number5202
    JournalSensors (Switzerland)
    Volume21
    Issue number15
    DOIs
    Publication statusPublished (VoR) - 1 Aug 2021

    Funding

    The authors submit sincere thanks and gratitude to the Ministry of Higher Education & Scientific Research, Al-Furat Al-Awsat Technical University (ATU), Engineering Technical College-Najaf in Iraq, for awarding a Postdoctoral Research Fellowship to work as visiting researchers at Istanbul Technical University (ITU) in Turkey. Meanwhile, this research has been produced, benefiting from the 2232 International Fellowship for Outstanding Researchers Program of TÜBİTAK (Project No: 118C276) conducted at Istanbul Technical University (ITU), and it was also supported in part by the Universiti Sains Islam Malaysia (USIM), Malaysia. Funding: The authors submit sincere thanks and gratitude to the Ministry of Higher Education & ScientificResearch,Al-FuratAl-AwsatTechnicalUniversity(ATU),EngineeringTechnicalCollege-Najaf in Iraq, for awarding a Postdoctoral Research Fellowship to work as visiting researchers at Istanbul Technical University (ITU) in Turkey. Meanwhile, this research has been produced, benefiting from the 2232 International Fellowship for Outstanding Researchers Program of TÜBİTAK (ProjectNo: 118C276) conducted atIstanbulTechnicalUniversity(ITU),anditwas also supportedinpartbytheUniversitiSainsIslamMalaysia(USIM),Malaysia.

    FundersFunder number
    Engineering Technical College-Najaf in Iraq
    EngineeringTechnicalCollege-Najaf in Iraq
    Ministry of Higher Education & ScientificResearch,Al-FuratAl-AwsatTechnicalUniversity
    Türkiye Bilimsel ve Teknolojik Araştirma Kurumu
    Ministry of Higher Education and Scientific Research
    Istanbul Teknik Üniversitesi118C276
    Universiti Sains Islam Malaysia
    Al-Furat Al-Awsat Technical University

      Keywords

      • Fifth generation (5G)
      • Handover (HO)
      • Handover control parameters (HCP)
      • Handover parameters optimisation (HPO)
      • Load balancing (LB)
      • Sixth generation (6G) networks

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