Fast Simulation for the Performance Evaluation of LDPC Codes using Fast Flat Histogram Method

Author

Kakakhail, S. ; Reynal, S. ; Declercq, D. ; Heinrich, V.

Author_Institution

ETIS, CNRS, Pontoise

fYear

2008

fDate

28-30 April 2008

Firstpage

1

Lastpage

5

Abstract

The quality of transmission in digital communication systems is usually measured by frame error rate (FER). The time taken by standard Monte Carlo (MC) simulation to estimate the FER increases exponentially with the increase in signal-to-noise ratio (SNR). In this correspondence, we present an Adaptive Importance Sampling (AIS) technique inspired by statistical physics called fast flat histogram (FFH) method to evaluate the performance of LDPC codes with a reduced simulation time. The FFH method employs Wang Landau algorithm based on a Markov Chain Monte Carlo (MCMC) sampler and we managed to decrease the simulation time by a factor of 13 to 173 for LDPC codes with block lengths up to 2640 bits.

Keywords

Markov processes; Monte Carlo methods; parity check codes; sampling methods; LDPC codes; Markov Chain Monte Carlo sampler; Wang-Landau algorithm; adaptive importance sampling technique; digital communication systems; fast flat histogram method; statistical physics; AWGN; Additive white noise; Digital communication; Error analysis; Gaussian noise; Histograms; Iterative decoding; Monte Carlo methods; Parity check codes; Signal to noise ratio;

fLanguage

English

Publisher

ieee

Conference_Titel

Sarnoff Symposium, 2008 IEEE

Conference_Location

Princeton, NJ

Print_ISBN

978-1-4244-1843-5

Type

conf

DOI

10.1109/SARNOF.2008.4520050

Filename

4520050