多径直接序列扩频信号伪随机序列的快速ICA盲估计

L. Shen, Zhijin Zhao
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Blind Estimation of the Pseudo-random Sequences of Direct Sequence Spread Spectrum Signals in Multi-Path Using Fast ICA
Spread spectrum signals are now widely used for secure communications, as well as for multiple access interference (MAI). They have many interesting properties, including low probability of interception. Indeed, DS/SS transmitters use a periodical pseudo-random sequence to modulate the baseband signal before transmission. A receiver which does not know the sequence can not demodulate the signal. Blind estimation of m-sequence is only discussed openly in the situation without multi-path interference and MAI so far. In this paper, we use the independent component analysis (ICA) to separate the data bits transmitted by different users in multi-path, and then identify m-sequence according to the triple correlation function (TCF) of m-sequence. The performance of this blind estimation is analyzed under Gaussian noise. Illustrative simulation examples are provided at last.
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