• DocumentCode
    2429143
  • Title

    MPSK demodulation algorithm based on pattern recognition

  • Author

    Kai-zhi Chen ; Ai-qun Hu

  • Author_Institution
    Coll. of Inf. Sci. & Eng., Southeast Univ., Nanjing
  • fYear
    2008
  • fDate
    7-11 June 2008
  • Firstpage
    182
  • Lastpage
    186
  • Abstract
    This paper proposes a MPSK demodulation algorithm based on pattern recognition theory, which processes MPSK order recognition, error estimate and signals demodulation together. The algorithm does not require prior information about MPSK order and the initial phase, but recognizes these parameters from received signals by pattern clustering method, then demodulates signals by pattern classification. Computer simulation results in terms of Bit-Error-Rate (BER) on additive white Gaussian noise (AWGN) channel show that the algorithm is able to effectively recognize MPSK order and optimal cluster centers. For QPSK, the correct recognition rate achieves 100% when Signal Noise Ratio (SNR) is 2 dB and 1280 symbols are used for clustering. Moreover, employing this algorithm, signal phase jitter is automatic cancelled, and BER performance overmatches original coherent demodulation that decision center points are fixed.
  • Keywords
    AWGN channels; demodulation; jitter; pattern recognition; phase shift keying; AWGN channel; MPSK demodulation algorithm; MPSK order recognition; additive white Gaussian noise channel; bit-error-rate; coherent demodulation; error estimation; optimal cluster centers; pattern classification; pattern clustering; pattern recognition; signal phase jitter; AWGN; Additive white noise; Bit error rate; Clustering algorithms; Computer errors; Demodulation; Pattern clustering; Pattern recognition; Signal processing; Signal to noise ratio; MPSK; PSK demodulation; automatic modulation classification; clustering; pattern recognition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks and Signal Processing, 2008 International Conference on
  • Conference_Location
    Nanjing
  • Print_ISBN
    978-1-4244-2310-1
  • Electronic_ISBN
    978-1-4244-2311-8
  • Type

    conf

  • DOI
    10.1109/ICNNSP.2008.4590336
  • Filename
    4590336