A New Method for Performance Evaluation of Turbo-Codes

In this paper, a new method for the performance evaluation of Turbo-Codes is presented. The method is based on estimating the Probability Density Function (pdf ) of the bit Log Likelihood Ratio (LLR) by using an exponential model. It is widely known that the pdf of the bit LLR is close to the normal density, and the proposed approach takes advantage of this property to simplify the calculations. The moment matching method is combined with the maximum entropy principle to estimate the parameters of the new model. A simple method for computing the confidence intervals for the estimated parameters, as well as for the Bit Error Rate (BER) is presented. The corresponding results are adopted to compute the number of samples that are required for a given precision of the estimated values. It is demonstrated that this method requires significantly fewer samples than the conventional Monte-Carlo (MC) simulation.