1. Hardware Architecture of a Gaussian Noise Generator Based on the Inversion Method
- Author
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R. Gutierrez, V. Torres, and Javier Valls
- Subjects
Random number generation ,Polynomial approximation ,Gaussian ,Gaussian tails ,White noise ,Virtex-II device ,Hardware resources ,Low hardware costs ,TECNOLOGIA ELECTRONICA ,Computer Science::Hardware Architecture ,symbols.namesake ,Hardware ,Random number generators ,Statistical tests ,Random noise ,Random sequence ,Electronic engineering ,Electrical and Electronic Engineering ,Piecewise polynomial approximation ,Additive white Gaussian noise (AWGN) ,Mathematics ,Hardware architecture ,Inversion methods ,Generator (computer programming) ,Inversion method ,Generation rate ,Inverse cumulative distribution functions ,Additive White Gaussian noise ,Lavarand ,Additive white Gaussian noise ,Gaussian noise ,symbols ,Gaussian noise (electronic) ,Algorithm - Abstract
In this brief, we present a hardware-based Gaussian noise generator (GNG) with low hardware cost, high generation rate, and high Gaussian tail accuracy. The proposed generator is based on a piecewise polynomial approximation of the inverse cumulative distribution function (ICDF). We propose to avoid the area-demanding barrel-shifter of the ICDF approximation by means of creating a new uniform random sequence from the uniform random number generator output. The GNG architecture has been implemented in field-programmable gate array devices, and the implementation results are compared with other published designs, achieving a higher deviation with fewer hardware resources. Our GNG generates 242 Msps of random noise and achieves a tail of 13.1 sigma with 442 slices, two multipliers, and two Block-RAM of a Virtex-II device. The generator output successfully passed commonly used statistical tests. © 2012 IEEE., This work was supported by Fondo Europeo de Desarrollo Regional and the Spanish Ministerio de Ciencia e Innovacion under Grant TEC2008-06787 and Grant TEC2011-27916. This brief was recommended by Associate Editor Y. Ha.
- Published
- 2012
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