Digital Implementation of a Pseudo-Random Noise Generator using Chaotic Maps

Random Number Generators (RNG) are an important component in modern digital secure communication systems and other applications. Chaotic systems have proven to be a good source of random signals for specific values of its control parameter. Iterated one-dimensional maps are simple dynamical systems suitable for chaos generation. The random or pseudorandom iteration of four variants of the scaled and discretized Bernoulli map is used to design a pseudo-random number generator (PRNG), which can produce binary sequences with a known statistical distribution. The values of the control parameter for which the system of multiple maps produces digital noise are determined by mathematical tools such as bifurcation diagrams, entropy function and the Lyapunov exponents. The proposed chaotic system is implemented in a compact digital FPGA architecture suitable for digital applications where PRNG's were needed.