Methods and apparatus for blind separation of radio signals

Details Methods and apparatus for blind separation of radio signals Methods and apparatus for blind separation of radio signals

1997-06-02

1999-09-28

Nguyen, Chau

Multiplex communications

Generalized orthogonal or special mathematical techniques

370334, H04J 400

Patent

active

059599669

ABSTRACT:
Multiple digital radio signals transmitted simultaneously at the same frequency are separated and the source signals recovered using blind source separation techniques. RF signals are received at a communications station (20) and downconverted to baseband signals. Blind Source Separation (BSS) based processes are applied to the baseband signals prior to demodulation to recover the source signals. To recover the source signals, a probability density function (PDF) model of the baseband source signal is generated (step 12) and an adaptation equation produced in accordance with the particular PDF model and BSS process (step 14). Using the known PDFs provides quicker adaptation to dynamic conditions. A separation matrix is learned by applying the adaptation equation to the baseband signals (step 16) and applied to the baseband signals to recover the source signals (step 18). Fading associated with mobile communications is overcome by using a sliding window of samples and updating a separation matrix sample by sample.

REFERENCES:
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patent: 5621730 (1997-04-01), Kelley
patent: 5706402 (1998-01-01), Bell
"Separation of Narrowband Digital Communication Signals: A Maximum Likelihood Approach", First IEEE Signal Processing Workshop On Signal Processing Advances In Wireless Communications, Apr. 16-18, 1997, Paris, France, sponsored by The IEEE Signal Processing Society.
A. Bell and T. Sejnowski, "Fast Blind Separation Based On Information Theory", Proceedings of the Internal Symposium on Nonlinear Theory and Application (NOTLA), pp. 43-47, Las Vegas Nevada, Dec. 10-14, 1995.
A. Bell and T. Sejnowski, "An Information-Maximisation Approach To Blind Separation and Blind Deconvolution", Neural Computation, 7(6):1129-1159, Feb. 1995.
B.A. Pearlmutter and L.C. Parra, "A Context-Sensitive Generalization of ICA", International Conference on Neural Information Processing, Hong Kong, Sep. 24-27, 1996.

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