A flexible high-throughput hardware architecture for a gaussian noise generator

In this paper a flexible, high-throughput, low-complexity additive white gaussian noise (AWGN) channel generator is presented. The proposed generator employs a Mersemie-Twister to generate a long random number uniformly distributed sequence and a Box-Muller transformation implementation to derive gaussian noise samples. Emphasis is given on developing a high-throughput approximation unit for die elementary functions required for die transformation. The proposed techniques are shown to lead to solutions that provide four samples per clock, which in turn can sustain throughputs of 584MSps, with moderate clock frequency and hardware complexity.