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Dynamic base stations selection method for passive location based on GDOP.

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|December 12, 2022
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Summary
This summary is machine-generated.

This study introduces a Dynamic Base Stations Selection (DBSS) method to improve mobile cellular network positioning accuracy. DBSS enhances accuracy by over 20% and reduces computational costs compared to fixed base station selection methods.

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Area of Science:

  • Mobile communication networks
  • Wireless positioning systems
  • Geomatics engineering

Background:

  • Passive location in mobile cellular networks presents challenges in achieving high positioning accuracy.
  • Base station selection is a critical factor influencing the precision of cellular network-based positioning.

Purpose of the Study:

  • To propose and evaluate a Dynamic Base Stations Selection (DBSS) method for enhancing passive location accuracy in mobile cellular networks.
  • To optimize base station selection using Geometric Dilution of Precision (GDOP) as the objective function.

Main Methods:

  • Analysis of base station layouts within cellular networks.
  • Development of DBSS algorithms, specifically DBSS4 and DBSS5, for dynamic base station selection.
  • Simulation experiments comparing DBSS algorithms against state-of-the-art methods.

Main Results:

  • The proposed DBSS method significantly reduces cumulative positioning error by over 20% compared to fixed base station selection.
  • DBSS achieves performance comparable to exhaustive search within cellular cells.
  • The method demonstrates improved efficiency with reduced running time and fewer floating-point operations (FLOPs).

Conclusions:

  • Dynamic Base Stations Selection (DBSS) offers a superior approach to passive location in mobile cellular networks.
  • DBSS provides a more accurate, efficient, and computationally less intensive solution for base station selection.
  • The proposed method is independent of specific localization algorithms, offering broad applicability.