Auto tuning self-optimization algorithm for mobility management in LTE-A and 5g hetnets

Citation

Alhammadi, Abdulraqeb Shaif Ahmed and Roslee, Mardeni and Alias, Mohamad Yusoff and Shayea, Ibraheem and Alraih, Saddam and Mohamed, Khalid Sheikhidris (2020) Auto tuning self-optimization algorithm for mobility management in LTE-A and 5g hetnets. IEEE Access, 8. pp. 294-304. ISSN 2169-3536

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Abstract

Ultra-dense networks represent the trend for future wireless 5G networks, which can provide high transmission rates in dense urban environments. However, a massive number of small cells are required to be deployed in such networks, and this requirement increases interference and number of handovers (HOs) in heterogeneous networks (HetNets). In such scenario, mobility management becomes an important issue to guarantee seamless communication while the user moves among cells. In this paper, we propose an auto-tuning optimization (ATO) algorithm that utilizes user speed and received signal reference power to adapt HO margin and time to trigger. The proposed algorithm aims to reduce the number of frequent HOs and HO failure (HOF) ratio. The performance of the proposed algorithm is evaluated through simulation with a two-tier model that consists of 4G and 5G networks. Simulation results show that the average rates of ping-pong HOs and HOF are significantly reduced by the proposed algorithm compared with other algorithms from the literature. In addition, the ATO algorithm achieves a low call drop rate and reduces HO delay and interruption time during user mobility in HetNets.

Item Type: Article
Uncontrolled Keywords: 5G mobile communication systems, Optimization, Heuristic algorithms, Tuning, Interference, Measurement, Adaptation models
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK5101-6720 Telecommunication. Including telegraphy, telephone, radio, radar, television
Divisions: Faculty of Engineering (FOE)
Depositing User: Ms Suzilawati Abu Samah
Date Deposited: 21 Dec 2020 07:43
Last Modified: 21 Dec 2020 07:43
URII: http://shdl.mmu.edu.my/id/eprint/7969

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