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Article detail · 2024 · article

Adaptive handover control parameters over voronoi-based 5G networks

YÖKSİS OpenAlex Open access · gold SJR Q1 JCR Q1
Year2024
Citations9OpenAlex
Percentile%73.7
FWCI1.051.00 = world average
Scopus (SJR)Q1
WoS (JCR)Q1

Data source split

  • YÖKSİSYÖKSİS article record
  • YÖKSİS venueEngineering Science and Technology, an International Journal
  • Catalog match (ISSN)Engineering Science and Technology, an International Journal
  • OpenAlexOpenAlex enrichment (abstract, citations, topics)

Abstract

OpenAlex English

Various speed scenarios such as high-speed travelling trains and connected drones over ultra-dense heterogeneous networks (HetNets) may result in a large number of handovers (HOs), which may cause further mobility challenges. Therefore, mobility robustness optimization (MRO) function has been proposed to contribute for detecting and correcting the mobility issues including too late HO, too early HO, and HO to the wrong cells. This function can be more effective in reducing these challenges related to mobility when proper optimization settings is performed for the handover control parameters (HCPs) (i.e., time-to-trigger (TTT) and handover margin (HOM)). In this paper, a trigger timer is proposed to reduce the unnecessary HOs. Meanwhile, this work proposes a weighted algorithm for optimizing the HCPs automatically based network experiences. The proposed algorithm rely on various factors for performing the optimization process. That includes, mobile movement speed, network traffic load, and the measurement report of the received signal reference power. Research work conducted by Matlab simulator that implement HetNets that consider Fifth Generation (5G) network and system settings based on 3GPP. Besides, 15 users were investigated using several mobile speed scenarios over Voronoi 5G network. The simulation results show that a significant achievement has been performed by the proposed algorithm as compared to the other algorithms investigated from the literature. The proposed algorithm has minimized the Radio Link Failure (RLF), Handover Ping-Pong (HOPP), Handover Probability (HOP), and handover interruption time by 8.8 %, 6.9 %, 6.7 %, and 344 %, respectively, lower than the other algorithms presented.

Topics

Citations

OpenAlex cited_by_count. Not a WoS or Scopus citation count; those sources have no separate column here.

9citationsOpenAlex · cited_by_count (cache / database)

11 publications in the local catalog that cite this work (OpenAlex reference match; not the full global list).

  1. 2024 An overview of mobility awareness with mobile edge computing over 6G network: Challenges and future research directionsCitations 46 · OpenAlex
  2. 2024 An overview of mobility awareness with mobile edge computing over 6G network: Challenges and future research directionsCitations 46 · OpenAlex
  3. 2025 Mobility and Handover Management in 5G/6G Networks: Challenges, Innovations, and Sustainable SolutionsCitations 22 · OpenAlex
  4. 2025 A Handover Decision Optimization Method Based on Data-Driven MLP in 5G Ultra-Dense Small Cell HetNetsCitations 20 · OpenAlex
  5. 2025 Machine learning for handover decision with mobile edge computing in 6G mobile network: a surveyCitations 4 · OpenAlex
  6. 2026 A Comprehensive Survey on Handover Management Techniques Toward Seamless Mobility in 5G and Beyond Heterogeneous NetworksCitations 3 · OpenAlex
  7. 2026 A Comprehensive Survey on Handover Management Techniques Toward Seamless Mobility in 5G and Beyond Heterogeneous NetworksCitations 3 · OpenAlex
  8. 2025 An overview of 6G wireless networksCitations 3 · OpenAlex
  9. 2025 An overview of 6G wireless networksCitations 3 · OpenAlex
  10. 2025 Machine learning for handover decision with mobile edge computing in 6G mobile network: a surveyCitations 2 · OpenAlex

Authors

6
  1. Waheeb Tashan 1
  2. IBRAHEEM ABDULLAH MOHAMMED SHAYEA 2
  3. Muntasir Sheikh 3
  4. HÜSEYİN ARSLAN İSTANBUL MEDİPOL ÜNİVERSİTESİ 4
  5. Ayman A. El-Saleh 5
  6. Ali Saad SAWSAN 6