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A User-Oriented Intelligent Access Selection Algorithm in Heterogeneous Wireless Networks.

Computational intelligence and neuroscience·2020
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Access-Selection Algorithm for Heterogeneous Wireless Networks Based on Uncertain Network Attribute Values.

Xiaoxue Guo1,2, Mohd Hasbullah Omar2, Khuzairi Mohd Zaini2

  • 1School of Science, Guangdong University of Petrochemical Technology, Maoming 525000, China.

Computational Intelligence and Neuroscience
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This study introduces a novel access-selection algorithm for heterogeneous wireless networks (HWNs) that handles uncertain network data. The new method helps mobile users select the best network, even with inaccurate information, leading to better performance.

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Area of Science:

  • Computer Science
  • Electrical Engineering
  • Telecommunications

Background:

  • Heterogeneous wireless networks (HWNs) integrate diverse network types like UMTS, LTE, and WLAN.
  • Ensuring optimal network selection for mobile users in HWNs is a significant research challenge.
  • Inaccurate network attribute values due to mobility and signal interference hinder traditional access-selection algorithms.

Purpose of the Study:

  • To design an advanced access-selection algorithm for HWNs that effectively manages uncertain network attribute values.
  • To enable mobile users to select the most suitable network for access despite data inaccuracies.
  • To improve user experience and network performance in dynamic wireless environments.

Main Methods:

  • Utilizes hesitant fuzzy theory to calculate network attribute values under uncertainty.
  • Employs the fuzzy analytic hierarchy process (FAHP) to determine the weights of network attributes.
  • Applies the hesitant fuzzy technique for order preference by similarity to ideal solution (TOPSIS) for network ranking.

Main Results:

  • The proposed algorithm successfully addresses the challenge of inaccurate network attribute values in HWNs.
  • Simulation results demonstrate improved network selection accuracy for mobile users.
  • The algorithm leads to enhanced gains for users accessing the most suitable network.

Conclusions:

  • The developed algorithm provides an effective solution for network access selection in uncertain HWN environments.
  • Hesitant fuzzy theory, FAHP, and TOPSIS integration offers a robust framework for complex network selection problems.
  • The findings contribute to optimizing user connectivity and resource utilization in heterogeneous wireless systems.