Parallel Gaussian White Noise Generator Based on Cellular Automaton Theory and Box Muller Algorithm

In order to simulate the wireless channel models, Gaussian white noise is needed to be generated. This paper proposes a parallel operation method based on cellular automation theory to obtain large pseudorandom numbers in high frequency. Furthermore, according to the Box Muller algorithm, the uniform distribution numbers are transformed to desired Gaussian white noise through curve matching function. During FPGA implementation, the high speed and real time noise generation is realized by combining the two methods.