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The transfer function is a fundamental concept in the analysis and design of linear time-invariant (LTI) systems. It offers a concise way to understand how a system responds to different inputs in the frequency domain. It serves as a bridge between the time-domain differential equations that describe system dynamics and the frequency-domain representation that facilitates easier manipulation and analysis.
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Robust Handover Optimization Technique with Fuzzy Logic Controller for Beyond 5G Mobile Networks.

Saddam Alraih1, Rosdiadee Nordin1, Asma Abu-Samah1

  • 1Department of Electrical, Electronic and Systems Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, Bangi 43600, Malaysia.

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|August 26, 2022
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Summary
This summary is machine-generated.

This study introduces a Robust Handover Optimization Technique with a Fuzzy Logic Controller (RHOT-FLC) for 5G and beyond networks. RHOT-FLC significantly improves handover performance metrics, reducing failures and latency for seamless mobile connectivity.

Keywords:
5G5G and beyondB5GHCPMROhandovermobility managementrobust handover techniqueself-optimizationsmall cells

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Area of Science:

  • Mobile Communications
  • Network Engineering
  • Wireless Networks

Background:

  • Mobility management is crucial for Quality of Service (QoS) in mobile networks.
  • 5G and beyond networks face increased complexity due to mmWave, small cells, and massive device growth.
  • Existing handover optimization techniques require enhancement for future network demands.

Purpose of the Study:

  • To propose a Robust Handover Optimization Technique with a Fuzzy Logic Controller (RHOT-FLC).
  • To automatically configure handover control parameters (HCPs) for improved mobility management.
  • To enhance seamless connectivity for user equipment (UE) in B5G networks.

Main Methods:

  • Developed RHOT-FLC utilizing Reference Signal Received Power (RSRP), Reference Signal Received Quality (RSRQ), and UE velocity.
  • Validated the technique through diverse mobility scenarios in B5G network simulations.
  • Evaluated performance using key metrics: HO probability (HOP), HO failure (HOF), HO ping-pong (HOPP), HO latency (HOL), and HO interruption time (HIT).

Main Results:

  • RHOT-FLC demonstrated superior performance compared to existing algorithms.
  • Achieved significant reductions: up to 95% in HOP, 95.8% in HOF, 97% in HOPP, 94.7% in HOL, and 95% in HIT.
  • Overall improvement of up to 95.5% across considered handover performance metrics.

Conclusions:

  • RHOT-FLC offers a robust and efficient solution for mobility management in 5G and beyond networks.
  • The fuzzy logic controller effectively optimizes handover parameters for enhanced user experience.
  • The proposed technique addresses critical challenges in future mobile network mobility.