A dynamic threshold computing method based on SOM neural network in frequency occupancy analysis

Miao Yang, Huiling Dai, Neng Ye

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Spectrum occupancy measurement and analysis is a very important aspect in frequency resource planning by the reason of frequency shortage for the increasing wireless systems. It is also useful in spectrum sensing in the context of cognitive radio, especially in unlicensed band. Given that, a dynamic decision threshold computing method based on SOM Neural Network in spectrum occupancy analysis is proposed in this paper. This method is designed to cluster sample data into different spaces by network self-learning without knowing the statistics of the measurement data. Simulation with pre-set data is given, and the results show the accuracy and the robustness of the proposed method. This dynamic method is validated with the data derived from the spectrum measurements of 806 - 960 MHz band in Beijing.

Original languageEnglish
Title of host publicationIET Seminar Digest
PublisherInstitution of Engineering and Technology
Pages153-158
Number of pages6
Edition3
ISBN (Print)9781849198455
DOIs
Publication statusPublished - 2014
Event10th International Conference on Wireless Communications, Networking and Mobile Computing, WiCOM 2014 - Beijing, China
Duration: 26 Sept 201428 Sept 2014

Publication series

NameIET Seminar Digest
Number3
Volume2014

Conference

Conference10th International Conference on Wireless Communications, Networking and Mobile Computing, WiCOM 2014
Country/TerritoryChina
CityBeijing
Period26/09/1428/09/14

Keywords

  • Data Processing
  • Dynamic Threshold
  • Occupancy Measurements
  • SOM Neural Network
  • Spectrum Sensing

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