Channel Propagation Model Identification for Spectrum Database: A Spark Based PVOS-ELM

Bo Zhou, Xiaopu Liu, Jianbin Li, Bo Bai, Wei Chen, Hui Tian

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Abstract

Spectrum database plays an increasingly important role in spectrum measurements and monitoring, which lays foundations for accurate and real-time spectrum sensing in future cognitive radio networks. A successful identification of the channel propagation model is of great importance to construct spectrum database so as to give an accurate picture of spectrum use in real-world environments. In this paper, based on the principle behind the voting-based online sequential extreme learning machine (VOS-ELM) and the Spark cloud computing platform, a novel parallel VOS-ELM (PVOS-ELM) algorithm will be proposed and implemented for real-time channel model identification in real-world propagation environment. The power measurement, kurtosis and skewness etc. will be used as features which are extracted from the received signal. Furthermore, the novel data parallel and task parallel processing schemes will be proposed to improve the computation efficiency of the proposed algorithm on Spark cloud computing platform. Extensive simulations and experiments with real-world data samples will be carried out. The experimental results illustrate that the proposed Spark based PVOS-ELM algorithm enjoys a significant accuracy performance improvement in channel identification and a much higher computation efficiency.

Original languageEnglish
Title of host publication2017 IEEE 85th Vehicular Technology Conference, VTC Spring 2017 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509059324
DOIs
Publication statusPublished - 14 Nov 2017
Externally publishedYes
Event85th IEEE Vehicular Technology Conference, VTC Spring 2017 - Sydney, Australia
Duration: 4 Jun 20177 Jun 2017

Publication series

NameIEEE Vehicular Technology Conference
Volume2017-June
ISSN (Print)1550-2252

Conference

Conference85th IEEE Vehicular Technology Conference, VTC Spring 2017
Country/TerritoryAustralia
CitySydney
Period4/06/177/06/17

Keywords

  • PVOS-ELM
  • Spark
  • Spectrum database
  • channel propagation model
  • real-time
  • spectrum monitoring

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Zhou, B., Liu, X., Li, J., Bai, B., Chen, W., & Tian, H. (2017). Channel Propagation Model Identification for Spectrum Database: A Spark Based PVOS-ELM. In 2017 IEEE 85th Vehicular Technology Conference, VTC Spring 2017 - Proceedings Article 8108216 (IEEE Vehicular Technology Conference; Vol. 2017-June). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/VTCSpring.2017.8108216