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

Author

Yang Zhou ; Ning Wang ; Xin Jiang

Author_Institution

Dept. of Inf. & Commun., Beijing Inst. of Technol., Beijing, China

fYear

2014

Firstpage

143

Lastpage

147

Abstract

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.

Keywords

Gaussian noise; field programmable gate arrays; random number generation; white noise; wireless channels; Box Muller algorithm; FPGA implementation; cellular automaton theory; curve matching function; high-speed noise generation; parallel Gaussian white noise generator; parallel operation method; pseudorandom numbers; real-time noise generation; uniform distribution numbers; wireless channel model; Algorithm design and analysis; Automata; Field programmable gate arrays; Generators; Polynomials; Vectors; White noise; Box Muller algorithm; cellular automation; matched curve; parallel; pseudorandom numbers;

fLanguage

English

Publisher

ieee

Conference_Titel

Wireless Communication and Sensor Network (WCSN), 2014 International Conference on

Print_ISBN

978-1-4799-7090-2

Type

conf

DOI

10.1109/WCSN.2014.36

Filename

7061712