A New Method for Performance Evaluation of Bit Decoding Algorithms Using Statistics of the Log Likelihood Ratio
Conference: TURBO - CODING - 2006 - 4th International Symposium on Turbo Codes & Related Topics; 6th International ITG-Conference on Source and Channel Coding
04/03/2006 - 04/07/2006 at Munich, Germany
Proceedings: TURBO - CODING - 2006
Pages: 6Language: englishTyp: PDFPersonal VDE Members are entitled to a 10% discount on this title
Abedi, Ali (Electrical and Computer Engineering Department, University of Maine, Orono, ME, USA)
Khandani, Amir K. (Electrical and Computer Engineering Department, University of Waterloo, Canada)
This paper presents a new method for the performance evaluation of bit decoding algorithms. 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. The proposed approach takes advantage of this property to present an efficient algorithm for the pdf estimation. The moment matching method is combined with the maximum entropy principle to estimate the underlying parameters. We present a simple method for computing the probabilities of the point estimates for the estimated parameters, as well as for the bit error rate. The corresponding results are used 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 as compared to the conventional Monte-Carlo simulation.