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基于循環(huán)累量不變量的MPSK信號調(diào)制識別算法

陳衛(wèi)東,  楊紹全

陳衛(wèi)東, 楊紹全. 基于循環(huán)累量不變量的MPSK信號調(diào)制識別算法[J]. 電子與信息學(xué)報, 2003, 25(3): 320-325.
引用本文: 陳衛(wèi)東, 楊紹全. 基于循環(huán)累量不變量的MPSK信號調(diào)制識別算法[J]. 電子與信息學(xué)報, 2003, 25(3): 320-325.
Chen Weidong, Yang Shaoquan. Algorithm for modultion classification of mpsk signals based on cyclic cumulant invariants[J]. Journal of Electronics & Information Technology, 2003, 25(3): 320-325.
Citation: Chen Weidong, Yang Shaoquan. Algorithm for modultion classification of mpsk signals based on cyclic cumulant invariants[J]. Journal of Electronics & Information Technology, 2003, 25(3): 320-325.

基于循環(huán)累量不變量的MPSK信號調(diào)制識別算法

Algorithm for modultion classification of mpsk signals based on cyclic cumulant invariants

  • 摘要: 提出一種新的循環(huán)累量不變量分類特征,來實現(xiàn)MPSK信號的調(diào)制樣式分類。新分類特征只利用了碼元速率的先驗信息,對基帶成型脈沖的形狀具有穩(wěn)健性;對MPSK基帶信號的時移、載波相位誤差、信號幅度變化具有不變性;并可抑制加性平穩(wěn)噪聲。利用循環(huán)時變累量的多信號選擇性,所提出的分類特征可實現(xiàn)多信號分類識別,理論分析和計算機仿真結(jié)果都證實了分類算法的有效性。
    Abstract: A new invariants classification feature based on cyclic temporary cumulant is proposed for classification of MPSK signals. The new feature only uses the symbol rate information, which is resistant to shaping pulse and invariant with respect to the time-translation, local carrier phase offset and amplitude scale of the baseband MPSK signals, and can suppress stationary additive noise. The signal selectivity of cyclic temporary cumulants makes it possible for the proposed feature to be applied to modulation classification of multi-signals. Theoretial analysis and extensive computer simulations show the efficiency of the proposed classification algorithm.
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  • Huang Chung-Yu, A. Polydoros, Likelihood methods for MPSK modulation classification, IEEE Trans. on Communications, 1995, COM-43(2/3/4), 1493-1504.[2]A. Swami, B. M. Sadler, Hierarchical digital modulation using cumulants, IEEE Trans. on Communications, 2000, COM-48(3), 416-429.[3]W.A. Gardner.[J].C. M. Spooner, Cyclic spectral analysis for signal detection and modulation recognition, MILCOM88, San Diego, CA.1988,:-[4]Y.K. Kim, C. L. Weber, Generalized single classifier with applications to SQPSK v.s. 2k PSK,MILCOM89, Boston, MA, 1989, Vol.3,754-759.[5]J. Reichert, Automatic classification of communication signals using higher order statistics,ICASSP92, San Francisco, 1992, Vol.5, 221-224.[6]J.G. Proakis, Digital Communication, Third Ed., New York, McGraw- Hill Book Co., 1995,chapter 4.[7]W.A. Gardner, C. M. Spooner, The cumulant theory of cyclostationary time-series, Part Ⅰ:Foundation, IEEE Trans. on Signal Processing, 1994, SP-42(12), 3387-3408.[8]C.M. Spooner, W. A. Gardner, The cumulant theory of cyclostationary time-series, Part Ⅱ:Development and Applications, IEEE Trans. on Signal Processing, 1994, SP-42(12), 3409-3429.[9]C.L. Nikias, Higher-Order Spectra Analysis--A Nonlinear Signal Processing Framework, Englewood Cliffs, New Jersey, PTR Prentice Hall, 1993, chapter 2. ［10］沈清,湯霖,模式識別導(dǎo)論,長沙,國防科技大學(xué)出版社,1991,25-35.
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出版歷程
  • 收稿日期:  2001-08-14
  • 修回日期:  2001-12-12
  • 刊出日期:  2003-03-19

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