Testing Error Correcting Codes by Multicanonical Sampling of Rare Events

Abstract

The idea of rare event sampling is applied to the estimation of the performance of error-correcting codes. The essence of the idea is importance sampling of the pattern of noises in the channel by Multicanonical Monte Carlo, which enables efficient estimation of tails of the distribution of bit error rate. The idea is successfully tested with a convolutional code.

References in corpus (3)

• Probing the tails of the ground state energy distribution for the directed polymer in a random medium of dimension $d=1,2,3$ via a Monte-Carlo procedure in the disorder
• Distribution of Lee-Yang zeros and Griffiths singularities in the $\pm J$ model of spin glasses
• A Monte Carlo Algorithm for Sampling Rare Events: Application to a Search for the Griffiths Singularity