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Channel Feature Extraction and Modeling Based on Principal Component Analysis

Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 857)

Abstract

The research aims to solve the problem of wireless channel feature extraction and modeling in mobile communications. According to the real channel measurement pulse results of three scenes, this study employs a digital signal processor to analyze the characterization of multi-path channel parameters and subsequently extract effective features. Through extracting feature parameters of channels in these scenes, we identify three different scenes, and analyze the trend and performance of different parameters on the channel features. The study then draws on principal component analysis to build a fingerprint of the wireless channel characteristic model. Finally, the research shows that the model features are in good agreement with the measured data.

Keywords

Channel characteristics Channel feature extraction Channel modeling Principal component analysis 

Notes

Acknowledgements

This work is supported by National Natural Science Foundation of China (No. 61661018 and 61662019); Natural Science Foundation of Hainan Province (No. 2016CXTD004); High Tech. of Key Research and Development Project of Hainan Province (No. ZDYF2016010); Scientific Research Foundation of Hainan University (No. kyqd1536); Key Project on Science Research of Higher School from Hainan Department of Education (No. Hnky2016ZD-5).

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Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  • Biyuan Yao
    • 1
  • Jianhua Yin
    • 1
  • Hui Li
    • 1
  • Hui Zhou
    • 1
  • Wei Wu
    • 2
  1. 1.College of Information Science and TechnologyHainan UniversityHaikouChina
  2. 2.Institute of Deep-sea Science and Engineering, Chinese Academy of SciencesSanyaChina

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