Additive White Gaussian Noise

Product Details

• Ask Xilinx About this Core

Documentation

• Additive White Gaussian Noise
• Release Notes (PDF)
• Core License Agreement (PDF)

Device Family Support

• Virtex-4 FX
• Virtex-4 LX
• Virtex-4 SX
• Virtex-II Pro
• Virtex-II
• Spartan-3

Requirements

• Xilinx ISE
• All Supported ISE Platforms

The Additive White Gaussian Noise (AWGN) module is often used to calculate BER curves for Forward Error Correction cores such as Reed-Solomon, Viterbi Decoder,Turbo Convolutional code, or Turbo Product code. The AWGN core is available as VHDL source code.

Key Features

• Probability density function (PDF) deviates less than 0.2 percent from the Gaussian PDF for |x| < 4.8o and is obtained from a closed-form expression
• Based on the Box-Muller algorithm and the central limit theorem
• Period of generated noise sequence is ~2190 = 1.57x1057 samples
• Power spectral density is flat
• SNR input ranges from 0.0 to 15.9 dB in steps of 0.1 dB and provides scaling to obtain desired variance