Research/Technical Note | | Peer-Reviewed

Mobility Management in Next Generation Wireless Networks

Received: 20 April 2024    Accepted: 28 May 2024    Published: 12 June 2024
Views:       Downloads:
Abstract

Living in a modern society without smart devices is impossible now a days. Every sector related to human lifestyle is either smart or controlled devices which was rare a decade back. Expectations are not limited to network connection but extend to mobility as well. As a result, mobility management becomes an essential and challenging task to accomplish. The revolution in wireless technologies expects more scalability and flexibility in resource management. Handover is one of the vital parts of radio resource management. Execution with perfection and optimization of the handover technique increases the reliability of the system deployed to meet the requirement of high mobility. The cell became small as the wireless cell size adjusted with the revolution of relevant technologies like fifth generation (5G) and beyond. Traffic profile and its density are always in a growing trend. This pattern draws the attention of ultra-dense networks (UDN). The UDN of small cells requires an extra number of handovers with higher accuracy and less delay in execution. In this context, this paper proposed an algorithm where a cross-examination to reduce unnecessary handover that improves the handover performance in next-generation wireless networks.

Published in American Journal of Networks and Communications (Volume 13, Issue 1)
DOI 10.11648/j.ajnc.20241301.16
Page(s) 75-83
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Mobility Management, Next Generation Wireless Networks, HetNet, Ping Pong Hand over, Wireless Communication

References
[1] Sapkale, P., Kolekar, U., “Mobility Management for 5G Mobile Networks”, International Journal of Computer Applications (0975-8887), 2018, Volume 182-No.26.
[2] Garzon, J. P., Hinojosa, O. A., Ameigeiras, P., Munoz, J. J. R., Maldonado, P. A., Soler, J. M. L., “Handover Implementation in a 5G SDN-based Mobile Network Architecture”, IEEE International Symposium on Personal, Indor and Mobile Radio Communication (PIRMC), 2016.
[3] Zhang, Z., “Research on Handover Technologies in 5th Generation Wireless Communication System”, Thesis, School of Electronic Information Engineering, Beijing Jiaotong University, Beijing, 100044, Chaina, 2018.
[4] Nyangaresi, V. O., Rodrigues, A. J., Abeka, S. O., “Secure Handover Protocol for High Speed 5G Networks”, International Journal Advanced Networking and Applications, 2020, Volume: 11, Issue: 06, Pages: 4429-4442 (2020), ISSN: 0975-0290.
[5] Arshad, R., Elsawy, H., Sorour, S., Al-Naffouri, T. Y., Alouini, M. S., “Handover Management in 5G and Beyond: A topology Aware Skipping Approach”, IEEE Access, 2016, Volume: 4, Pages: 9073-9081.
[6] Giust, F., Cominardi, L., Bernardos, C. J., “Distributed Mobility Management for future 5G networks: overview and analysis of existing approaches”, University Carlos III of Madrid, Spain.
[7] lin, C. C., Sandrasegaran, K., Ramli, H. A. M., Basukala, R., “Optimized Performance Evaluation of LTE Hard Handover Algorithm with Average RSRP Constant”, International Journal of Wireless & Mobile Networks (IJWMN), 2011, Volume: 3, No. 2.
[8] Zheng, W., Zhang, H., Chu, X., Wen, X., “Mobility Robustness Optimization in Self-organizing LTE Femtocell Networks”, EURASIP Journal on Wireless Communications and Networking, 2013.
[9] Wang, D., Qiu, A., Partani, S., Zohu, Q., Schotten, D., “Mitigating Unnecessary Handovers in Ultra-Dense Networks through Machine Learning-based Mobility Prediction”, German Research Center for Artificial Intelligence (DFKI GmbH), 2023, Kaiserslautern, Germany.
[10] Ashour, A. F., Fouda, M. M., “AI-Based Approaches for Handover Optimization in 5G New Radio and 6G Wireless Networks”, International Conference on Computer Science, Information Technology and Engineering (ICCoSITE), 2023.
[11] Mandour, M., Gebali, F., Elbayoumy, A. D., Hamid, G. M. A., Abdelaziz, A., “Handover Optimization and User Mobility Prediction in LTE Femtocells Network”, Department of Electrical and Computer Engineering, University of Victoria, Canada.
[12] Mahamod, U., Mohamad, H., Shayea, I., Othman, M., Asuhaimi, F. A., “Handover parameter for self optimisation in 6G mobile networks: A survey”, Alexandria Engineering Journal, 2023, 78, 104-119.
[13] Saad, W. K., Shayea, I., Hamza, B. J., Mohamad, H., Daradkeh, Y. I., Jabbar, W. A. “Handover Parameters Optimisation Techniques in 5G Networks”, Sensors, 2021, 21, 5202.
[14] Bilen, T., Canberk, B., Chowdhury, K. R., “Handover Management in Software-Defined Ultra-Dense 5G Networks”, IEEE Network, 2017.
[15] Chu, H. C., Wong, C. E., Cheng, W. M., Lai, H. C., “User QoS-Based Optimized Handover Algorithm for Wireless Networks”, Sensors, 2023, 23, 4877.
[16] Khan, M., Han, K., “An Optimized Network Selection and Handover Triggering Scheme for Heterogeneous Self-Organized Wireless Networks”, Mathematical Problems in Engineering, 2014, Volume 2014, Article ID 173068.
[17] Hsieh, IP., Kao, S. J., “Handoff optimization in 802.11 wireless networks”, EURASIP Journal on Wireless Communications and Networking, 2011.
[18] Ajao, J., Adebayo, A., Joshua, J., Ebiesuwa, O., Ihedioha, U., Ugwu, N., Mathew, D. E., “A HANDOVER SELF-OPTIMIZING MATHEMATICAL MODEL: A REVIEW IN MOBILE WIRELESS NETWORKS”, International Research Journal of Modernization in Engineering Technology and Science, 2021, Volume:03/Issue:04.
[19] Ahasan, M. R., Haque, M. S., Alam, M. G. R., “Supervised Learning based Mobile Network Anomaly Detection from Key Performance Indicator (KPI) Data”, IEEE Region 10 Symposium (TENSYMP), 2023, Mumbai, India, pp. 1-6, https://doi.org/10.1109/TENSYMP54529.2022.9864371
[20] Ahasan, M. R., Momen, M. F., Haque, M. S., Akram, M. R., Alam, G. R., Uddin, M. Z., “Benchmarking Unsupervised Machine Learning for Mobile Network Anomaly Detection”, International Conference on Innovations in Science, Engineering and Technology (ICISET), 2022, Chittagong, Bangladesh, pp. 468-473, https://doi.org/10.1109/ICISET54810.2022.9775904
Cite This Article
  • APA Style

    Islam, M. S., Chowdhury, S. A. H. (2024). Mobility Management in Next Generation Wireless Networks. American Journal of Networks and Communications, 13(1), 75-83. https://doi.org/10.11648/j.ajnc.20241301.16

    Copy | Download

    ACS Style

    Islam, M. S.; Chowdhury, S. A. H. Mobility Management in Next Generation Wireless Networks. Am. J. Netw. Commun. 2024, 13(1), 75-83. doi: 10.11648/j.ajnc.20241301.16

    Copy | Download

    AMA Style

    Islam MS, Chowdhury SAH. Mobility Management in Next Generation Wireless Networks. Am J Netw Commun. 2024;13(1):75-83. doi: 10.11648/j.ajnc.20241301.16

    Copy | Download

  • @article{10.11648/j.ajnc.20241301.16,
      author = {Md. Shohidul Islam and Shah Ariful Hoque Chowdhury},
      title = {Mobility Management in Next Generation Wireless Networks},
      journal = {American Journal of Networks and Communications},
      volume = {13},
      number = {1},
      pages = {75-83},
      doi = {10.11648/j.ajnc.20241301.16},
      url = {https://doi.org/10.11648/j.ajnc.20241301.16},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajnc.20241301.16},
      abstract = {Living in a modern society without smart devices is impossible now a days. Every sector related to human lifestyle is either smart or controlled devices which was rare a decade back. Expectations are not limited to network connection but extend to mobility as well. As a result, mobility management becomes an essential and challenging task to accomplish. The revolution in wireless technologies expects more scalability and flexibility in resource management. Handover is one of the vital parts of radio resource management. Execution with perfection and optimization of the handover technique increases the reliability of the system deployed to meet the requirement of high mobility. The cell became small as the wireless cell size adjusted with the revolution of relevant technologies like fifth generation (5G) and beyond. Traffic profile and its density are always in a growing trend. This pattern draws the attention of ultra-dense networks (UDN). The UDN of small cells requires an extra number of handovers with higher accuracy and less delay in execution. In this context, this paper proposed an algorithm where a cross-examination to reduce unnecessary handover that improves the handover performance in next-generation wireless networks.},
     year = {2024}
    }
    

    Copy | Download

  • TY  - JOUR
    T1  - Mobility Management in Next Generation Wireless Networks
    AU  - Md. Shohidul Islam
    AU  - Shah Ariful Hoque Chowdhury
    Y1  - 2024/06/12
    PY  - 2024
    N1  - https://doi.org/10.11648/j.ajnc.20241301.16
    DO  - 10.11648/j.ajnc.20241301.16
    T2  - American Journal of Networks and Communications
    JF  - American Journal of Networks and Communications
    JO  - American Journal of Networks and Communications
    SP  - 75
    EP  - 83
    PB  - Science Publishing Group
    SN  - 2326-8964
    UR  - https://doi.org/10.11648/j.ajnc.20241301.16
    AB  - Living in a modern society without smart devices is impossible now a days. Every sector related to human lifestyle is either smart or controlled devices which was rare a decade back. Expectations are not limited to network connection but extend to mobility as well. As a result, mobility management becomes an essential and challenging task to accomplish. The revolution in wireless technologies expects more scalability and flexibility in resource management. Handover is one of the vital parts of radio resource management. Execution with perfection and optimization of the handover technique increases the reliability of the system deployed to meet the requirement of high mobility. The cell became small as the wireless cell size adjusted with the revolution of relevant technologies like fifth generation (5G) and beyond. Traffic profile and its density are always in a growing trend. This pattern draws the attention of ultra-dense networks (UDN). The UDN of small cells requires an extra number of handovers with higher accuracy and less delay in execution. In this context, this paper proposed an algorithm where a cross-examination to reduce unnecessary handover that improves the handover performance in next-generation wireless networks.
    VL  - 13
    IS  - 1
    ER  - 

    Copy | Download

Author Information
  • Electronics and Telecommunication Engineering, Rajshahi University of Engineering and Technology, Rajshahi, Bangladesh

  • Electronics and Telecommunication Engineering, Rajshahi University of Engineering and Technology, Rajshahi, Bangladesh

  • Sections