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基于多子波的CDMA系統(tǒng)

潘進,  焦李成,  方洋旺

潘進, 焦李成, 方洋旺. 基于多子波的CDMA系統(tǒng)[J]. 電子與信息學報, 2002, 24(9): 1167-1171.
引用本文: 潘進, 焦李成, 方洋旺. 基于多子波的CDMA系統(tǒng)[J]. 電子與信息學報, 2002, 24(9): 1167-1171.
Pan Jin, Jiao Licheng, Fang Yangwang. CDMA system based on multiWavelet[J]. Journal of Electronics & Information Technology, 2002, 24(9): 1167-1171.
Citation: Pan Jin, Jiao Licheng, Fang Yangwang. CDMA system based on multiWavelet[J]. Journal of Electronics & Information Technology, 2002, 24(9): 1167-1171.

基于多子波的CDMA系統(tǒng)

CDMA system based on multiWavelet

  • 摘要: 將多子波的分析濾波器、預處理以及平衡化等方面的最新研究成果應用于通信領域,提出了多子波碼分多址(MW-CDMA)通信系統(tǒng)的理論框架。在MW-CDMA中,系統(tǒng)首先將接收信號投影到相互正交的子波空間上,然后在各子波空間中進行多用戶解調(diào)。理論分析系和仿真結果表明,這種系統(tǒng)可以很好地抑制多址干擾和環(huán)境噪聲。同時也為減少解碼的計算量提供了新的思路。
    Abstract: A MultiWavelet-based Code-Division Multiple-Access (MW-CDMA) scheme is presented based on the application of recent results in multiwavelet analysis filter, preprocessing and balancing to communications area. In MW-CDMA, at first, the received signal is decomposed into the components in the orthogonal wavelet spaces, and then the multiuser demodulation is implemented in each wavelet space. Theoretical analyses and experimental results show that MW-CDMA systems suppress multiple-access interference and ambient noise well. Moreover, the scheme gives a new guideline of thought to reduce the computation for demodulating.
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  • S. Verd, Multiuser Detection, Cambridge, U K, Cambridge Univ. Press, 1998, Chapter4～Chapter7.[2]G. Woodward, B. S. Vuctic, Adaptive detection for DS-CDMA, Proc. IEEE, 1998, 86(7), 1413-1433.[3]X. Wang, H. V. Poor. Blind joint equalization and multiuser detection for DS-CDMA in unknowncorrelated noise, IEEE Trans. on Circuits and Systems-II: Analog and Digital Processing, 1999,CAS-II-46(7), 886-895.[4]A. Duel-Hallen, A family of multiuser decision-feedback detectors for synchronous code-divisionmultiple access channel, IEEE Trans. on Commun., 1995, COM-43(2/3/4), 421-434.[5]A.N. Akansu, P. Duhamel, X. Lin, Marc de Courville, Orthogonal transmultiplexers in communication: A review, IEEE Trans. on Signal Processing, 1998, SP-46(4), 979-995.[6]Q. Jiang, Orthogonal multiwavelets with optimum time-frequency resolution, IEEE Trans. onSignal Processing, 1998, SP-46(4), 830-844.[7]J. Pan, L. Jiao, L. Chen, Construction of orthogonal multiwavelets with short sequence via geneticalgorithm, Progress in Natural Science, 2000, 10(4), 294-301.[8]X.G. Xia, A new prefilter design for discrete multiwavelet transforms, IEEE Trans. on SignalProcessing, 1998, SP-46(6), 1558-1570.[9]X. Yang, L. Jiao, J. Pan, Prefilter for multiwavelet neural network, Progress in Natural Science,2000, 10(10), 780-786.[10]J. Lebrun, M. Vetterli, Balanced multiwavelets theory and design, IEEE Trans. on Signal Processing, 1998, SP-46(4), 1119-1125.[11]J.S. Geronimo, D. P. Hardin, P. R. Massopust. Fractal functions and wavelet expansions basedon several scaling functions, Journal of Approximation Theory, 1994, 78(3), 373-401.
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  • 文章訪問數(shù):  1886
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出版歷程
  • 收稿日期:  2001-02-11
  • 修回日期:  2001-08-17
  • 刊出日期:  2002-09-19

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