Non-supervised Rule for Direct Sequence Spread Spectrum Signal Sequence Acquisition

Having not the apriority knowledge about the DSSS signal in the non-cooperation condition, we proposed a Non-Supervised neural network algorithm to detect and identify the PN sequence. A cognitive learning algorithms for estimation the direct sequence spread spectrum (DSSS) signal pseudo-noise (PN) sequence is presented. The non-supervised learning algorithm is proposed according to the Kohonen rule in SOFM. The blind algorithm can also estimation the PN sequence in low SNR and computer simulation demonstrated that the algorithm is effective. Comparing the traditional algorithm based on slip-correlation, the cognitive algorithm´s bit error rate (BER) and complexity is lower.