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Use APEX Neural Networks to Extract the PN Sequence in Lower SNR DS-SS Signals

  • Tianqi Zhang
  • Zengshan Tian
  • Qianbin Chen
  • Xiaokang Lin
  • Zhengzhong Zhou
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4114)

Abstract

This paper introduces an unsupervised adaptive principal components analysis (APEX) neural network (NN) for blind pseudo noise (PN) sequence extraction of lower signal to noise ratios (SNR) direct sequence spread spectrum (DS-SS) signals. The proposed method is based on eigen-analysis of DS-SS signals. As the eigen-analysis method is based on the decomposition of autocorrelation matrix of signals, it has computational defects when the signal vectors became longer, etc. So, we introduce the APEX NN to extract the PN sequence blindly. We also make complexity analysis of the proposed method and comparison with the other methods. Theoretical analysis and computer simulations verify the effectiveness of the method.

Keywords

Neural Network Method Batch Method Autocorrelation Matrix Direct Sequence Spread Spectrum Receive Signal Vector 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Tianqi Zhang
    • 1
  • Zengshan Tian
    • 1
  • Qianbin Chen
    • 1
  • Xiaokang Lin
    • 2
  • Zhengzhong Zhou
    • 3
  1. 1.School of Communication and Information Engineering / Research Centre for Optical Internet and Wireless Information Networks (COIWIN), Chongqing University of Posts and Telecommunications (CQUPT), Chongqing, 400065China
  2. 2.Graduate School at Shenzhen of Tsinghua University, Shenzhen 518055China
  3. 3.School of Communication and Information Engineering, University of Electronic Science, and Technology of China (UESTC), Chengdu 610054China

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