Lossless source coding using repeat-accumulate codes

Design of good repeat-accumulate (RA) codes for data compression has been possible by using extrinsic information transfer (EXIT) charts. EXIT charts could also predict the average compression rate achieved by the RA code. However, for RA source codes the compression rate is a random variable and to the best of our knowledge simulation is the only known way to find the probability mass function (pmf) of the compression rate. In this paper, we present a tool to evaluate this pmf when the inner code is a single memory recursive convolutional code. Considering regular RA codes we then study the effect of two parameters on the accuracy of the evaluated pmf: the block length and the rate of the outer code. Simulation results show that this evaluation is fairly accurate for short block length systems and high-rate outer codes.