A Chaos-Based High Quality PN Sequence Generator

Chaos-based PN sequence generators are widely investigated recently. Concrete implementation of theses chaos-based generators usually have some problems because any processor or chips are computation precision restricted, which greatly effects the statistical properties of a chaotic PN sequence. This paper proposes a couple chaotic systems based stochastic bit quantification algorithm, which extends the period of the chaotic PN sequence and strengthens the anti neural network based adaptive parameter attack ability under precision restricted condition. The balance and correlation properties of the generated sequence are analyzed. The sequence is proved to be a binary Bernoulli sequence and the side lobes of odd/even auto and cross correlation are proved to obey normal distribution N(0, 1/N). Experimental results show that the algorithm has excellent statistical properties, and can be used to generate PN sequence with higher quality than conventional schemes.