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  • Research Article
  • Open Access

An Iterative Soft Bit Error Rate Estimation of Any Digital Communication Systems Using a Nonparametric Probability Density Function

EURASIP Journal on Wireless Communications and Networking20092009:512192

  • Received: 22 July 2008
  • Accepted: 3 March 2009
  • Published:


In general, performance of communication system receivers cannot be calculated analytically. The bit error rate (BER) is thus computed using the Monte Carlo (MC) simulation (Bit Error Counting). It is shown that if we wish to have reliable results with good precision, the total number of transmitted data must be conversely proportional to the product of the true BER by the relative error of estimate. Consequently, for small BERs, simulation results take excessively long computing time depending on the complexity of the receiver. In this paper, we suggest a new means of estimating the BER. This method is based on an estimation, in an iterative and nonparametric way, of the probability density function (pdf) of the soft decision of the received bit. We will show that the hard decision is not needed to compute the BER and the total number of transmitted data needed is very small compared to the classical MC simulation. Consequently, computing time is reduced drastically. Some theoretical results are also given to prove the convergence of this new method in the sense of mean square error (MSE) criterion. Simulation results of the suggested BER are given using a simple synchronous CDMA system.


  • Mean Square Error
  • Probability Density Function
  • Monte Carlo
  • Transmitted Data
  • Monte Carlo Simulation

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Authors’ Affiliations

Institut TELECOM, TELECOM Bretagne, UMR CNRS 3192 Lab-STICC, Technopôle Brest-Iroise CS 83818, 29238 Brest Cedex3, France
Université Européenne de Bretagne, (UeB), France
Institut TELECOM, TELECOM Bretagne, Technopôle Brest-Iroise CS 83818, 29238 Brest Cedex3, France
Laboratoire CRISTAL, Ecole Nationale de Sciences de L'Informatique (ENSI), Campus Universitaire de la Manouba, 2010 Manouba, Tunisia


© Samir Saoudi et al. 2009

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.