Abstract
A neural network model is described which simulate the Parallel Matching Filtering (PMF) for Direct Sequence Spread Spectrum (DSSS) signal acquisition. This system is based on training the Counter Propagation Network (CPN) in all half chip phase shifts of the Pseudo Noise (PN) code. The trained network can be used at the receiver for the signal acquisition. The CPN performance in Additive Wight Gaussian Noise (AWGN) channel is evaluated. Computer simulations carried on maximal length sequences of length N=256, show that the proposed system can effectively decide the half chip phase shift of the received code even at much lower Signal to Noise ration (S/N) until S/N = -27.74dB. This model has a simple architecture, so can be realized in a simple hardware. This makes the neural network based acquisition technique faster and more robust than the other conventional acquisition techniques.
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© 2004 Springer-Verlag Berlin Heidelberg
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Elhabian, T., Zhang, B., Shao, D. (2004). Neural Direct Sequence Spread Spectrum Acquisition. In: Yin, FL., Wang, J., Guo, C. (eds) Advances in Neural Networks - ISNN 2004. ISNN 2004. Lecture Notes in Computer Science, vol 3174. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-28648-6_44
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DOI: https://doi.org/10.1007/978-3-540-28648-6_44
Publisher Name: Springer, Berlin, Heidelberg
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