A Novel Handoff Necessity Estimation Approach Based on Travelling Distance

Madaan, Jyoti; Kashyap, Indu

doi:10.5815/ijisa.2018.01.06

Cited by 5 publications

(2 citation statements)

References 10 publications

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“…In order to execute a handover, it is necessary to determine the need for a handover, select the appropriate target for the handover, the timing of the handover, and define the conditions that will trigger the handover process [21][22][23]. Handover necessity estimation (HNE) is the process of determining whether a handover is necessary based on various factors, such as resource availability, the complexity of the task, and potential risks [24,25]. Handover target selection (HTS) involves selecting the most suitable target channel for the handover, considering factors such as the target channel capacity and capabilities [26,27].…”

Section: Types Of Handovermentioning

confidence: 99%

Performance evaluation of handover triggering condition estimation using mobility models in heterogeneous mobile networks

Malik,

Jamshed,

Nauman

et al. 2024

IET Networks

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Heterogeneous networks (HetNets) refer to the communication network, consisting of different types of nodes connected through communication networks deploying diverse radio access technologies like LTE, Wi‐Fi, Zigbee, and Z‐wave, and using different communication protocols and operating frequencies. Vertical handover, is the process of switching a mobile device from one network type to another, such as from a cellular network to a Wi‐Fi network, and is critical for ensuring a seamless user experience and optimal network performance, within the handover process handover triggering estimation is one of the crucial step affecting the overall performance. A mathematical analysis is presented for the handover triggering estimation. The performance evaluation shows significant improvement in the probability of successful handover using the proposed handover triggering condition based on speed, distance, and different mobility models. The handover triggering condition is optimised based on the speed of the mobile node, handover completion time, and the coverage range of the current and the target networks of the HetNet node, with due consideration of the mobility model.

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Section: Types Of Handovermentioning

confidence: 99%

Performance evaluation of handover triggering condition estimation using mobility models in heterogeneous mobile networks

Malik,

Jamshed,

Nauman

et al. 2024

IET Networks

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“…More accurate decisions entail higher system performance. Several studies have been conducted to enhance appropriate HO decisions such as in [67]- [72], [82]- [92]. The serving cell decides to HO to a target cell for UEs if the applied algorithm meets the defined requirements, as shown in Fig.…”

Section: E Handover Decision In Hetnetsmentioning

confidence: 99%

Mobility Robustness Optimization in Future Mobile Heterogeneous Networks: A Survey

et al. 2022

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Ensuring reliable and stable communication during the movements of mobile users is one of the key issues in mobile networks. In the recent years, several studies have been conducted to address the issues related to Handover (HO) self-optimization in Heterogeneous Networks (HetNets) for Fourth Generation (4G) and Fifth Generation (5G) mobile networks. Various solutions have been developed to determine or estimating the optimum and ideal settings of Handover Control Parameters (HCPs), such as Time-To-Trigger (TTT) and Handover Margin (HOM). However, the complexity, high requirements, and the upcoming structure of ultra-dense HetNets require more advanced HO self-optimization techniques for future implementation. This paper studies HO self-optimization techniques that may implemented in the next-generation mobile HetNets by reviewing state-of-the-art algorithms. The solutions discussed in this survey are more focus on Mobility Robustness Optimization (MRO), which is a significant self-optimization function in 4G and 5G mobile networks. The applied solutions will preserve the continuous connection between the User Equipment (UE) and eNBs during UE mobility, thereby enhancing connection quality. The various algorithms and techniques applied to HO have revealed different outcomes. This paper discusses the pros and cons of these techniques, and further examines HO self-optimization challenges and solutions. New future directions for the implementation of HO self-optimization are also identified. This survey will contribute to the understanding of the issues related to mobility management, particularly in relation to the self-optimization of HO control parameters in future mobile HetNets.

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