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An Interface Setup Optimization Method Using a Throughput Estimation Model for Concurrently Communicating Access

Fatema Akhter1, Nobuo Funabiki1, Ei Ei Htet1

  • 1Graduate School of Natural Science and Technology, Okayama University, Okayama 700-8530, Japan.

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|July 29, 2023
PubMed
Summary
This summary is machine-generated.

This study introduces an optimized method for wireless networks to improve performance by adjusting access point (AP) transmission power and channel bonding (CB) or non-CB settings. The new approach efficiently maximizes throughput in dense networks, overcoming limitations of previous methods.

Keywords:
channel bondinginterface setup optimizationsignal-to-interference ratiothroughput estimation modelwireless local area network

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Area of Science:

  • Computer Science
  • Electrical Engineering
  • Network Engineering

Background:

  • Dense IEEE 802.11 wireless local-area networks (WLANs) face performance degradation due to radio interference from adjacent access points (APs).
  • Existing AP transmission power optimization methods require extensive receiving signal strength (RSS) measurements, becoming computationally intensive with increasing numbers of APs.
  • Previous methods often overlook the benefits of non-channel bonding (non-CB) in high-interference environments, potentially limiting performance.

Purpose of the Study:

  • To develop an efficient AP interface setup optimization method for concurrently communicating APs.
  • To enhance average signal-to-interference ratio (SIR) and maximize total throughput in large-scale wireless networks.
  • To integrate channel bonding (CB) and non-CB selection with power optimization, avoiding costly RSS measurements.

Main Methods:

  • Proposed an AP interface setup optimization method utilizing a throughput estimation model.
  • The model estimates RSS based on distance and obstacles, enabling SIR calculation without direct measurements.
  • Optimized AP settings by selecting between CB/non-CB and maximum/minimum power for each AP.

Main Results:

  • The proposed method successfully optimizes AP interface setups for large-scale wireless networks.
  • Experimental evaluations using Raspberry Pi and Linux PCs demonstrated the method's effectiveness across diverse network topologies.
  • The optimized setups consistently achieved the highest total throughput compared to other configurations.

Conclusions:

  • The developed throughput estimation model provides an efficient and cost-effective solution for optimizing dense WLANs.
  • The method's ability to select optimal AP power and channel bonding strategies significantly improves network performance.
  • This approach offers a practical solution for enhancing the performance of large-scale wireless networks in real-world environments.