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Research on Distributed 5G Signal Coverage Detection Algorithm Based on PSO-BP-Kriging.

Tingli Xiang1, Hongjun Wang2

  • 1Institute of Electronic Countermeasure, National University of Defense Technology, Hefei 230037, China. xiangtl1994@gmail.com.

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|December 15, 2018
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Summary

A new algorithm using distributed sensors and AI improves 5G mobile communication network signal coverage detection. This method enhances accuracy over traditional road tests, offering practical application potential.

Keywords:
5G mobile communication networkPSO-BP-Krigingdistributed sensor networkinterpolationneural network

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Area of Science:

  • Telecommunications Engineering
  • Computer Science
  • Geostatistics

Background:

  • Traditional road testing for 5G signal coverage is limited.
  • Accurate detection of 5G network signal coverage is crucial for performance optimization.

Purpose of the Study:

  • To propose a novel signal coverage detection algorithm for 5G mobile communication networks.
  • To overcome the limitations of existing road test methods.

Main Methods:

  • Utilized a distributed sensor network for collecting received signal strength data.
  • Modified neural network objective function with variogram function.
  • Optimized neural network weights using an improved particle swarm optimization algorithm.
  • Employed neural network for interpolating coverage blind zones.

Main Results:

  • The proposed algorithm demonstrated superior performance in detecting 5G signal coverage compared to other methods.
  • Successfully combined sensor data with interpolation estimates for effective coverage mapping.
  • Simulation results confirmed the algorithm's feasibility and practical application prospects.

Conclusions:

  • The developed algorithm offers a more accurate and feasible approach to 5G signal coverage detection.
  • This method addresses key limitations of traditional testing techniques.
  • The approach shows significant potential for real-world deployment in telecommunications.