Blind Estimation of Pseudo-random Sequences of the Carrier Modulated Direct Sequence Spread Spectrum Signals in Asynchronous Uplink System Using Space-Time Complex-ICA

Without the knowledge of the users’ carrier frequency or the channel parameters, this paper proposes a new arithmetic to blind estimate the pseudo-random sequences, based on the space-time complex independent component analysis (ST-CICA), phase lock loop (PLL) and principal component analysis (PCA). The received carrier modulated signals are firstly separated by the ST-CICA, while the multi-path interference, multiple access interference and near-far effect are cancelled. PLL and PCA will be utilized on the separated signal, in order to estimate the pseudo-random sequences, the carrier frequencies and the data of users. This new arithmetic of blind estimation works well in low signal-to-noise ratio (SNR) environment, because of well utilizing of antenna array diversity gain and spreading gain. The performance of blind estimation is analyzed under Gaussian noise. Illustrative simulation examples were provided at last.

[1]  A. Yongacoglu,et al.  Application of noisy-independent component analysis for CDMA signal separation , 2004, IEEE 60th Vehicular Technology Conference, 2004. VTC2004-Fall. 2004.

[2]  E. R. Adams,et al.  Detection and blind identification of m-sequence codes using higher order statistics , 1999, Proceedings of the IEEE Signal Processing Workshop on Higher-Order Statistics. SPW-HOS '99.

[3]  Lin Xiaokang,et al.  A neural network approach to blind-estimation of PN spreading sequence in lower SNR DS/SS signals , 2004, Proceedings 7th International Conference on Signal Processing, 2004. Proceedings. ICSP '04. 2004..

[4]  Xiaokang Lin,et al.  A Modified PCA Neural Network to Blind Estimation of the PN Sequence in Lower SNR DS-SS Signals , 2005, ISNN.

[5]  Zhao Zhijing,et al.  Blind Estimation of the Pseudo-random Sequences of Direct Sequence Spread Spectrum Signals in Multi-Path Using Fast ICA , 2009, 2009 Pacific-Asia Conference on Circuits, Communications and Systems.

[6]  Zhenwei Shi,et al.  A fast fixed-point algorithm for complexity pursuit , 2005, Neurocomputing.

[7]  Gilles Burel,et al.  Blind estimation of the pseudo-random sequence of a direct sequence spread spectrum signal , 2000, MILCOM 2000 Proceedings. 21st Century Military Communications. Architectures and Technologies for Information Superiority (Cat. No.00CH37155).

[8]  L. B. Milstein,et al.  Theory of Spread-Spectrum Communications - A Tutorial , 1982, IEEE Transactions on Communications.

[9]  Hualiang Li,et al.  A Class of Complex ICA Algorithms Based on the Kurtosis Cost Function , 2008, IEEE Transactions on Neural Networks.

[10]  Aapo Hyvärinen,et al.  ICA of complex valued signals: a fast and robust deflationary algorithm , 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium.