A new performance evaluation metric for sub-optimal iterative decoders

  • Authors:

  • Ashwani Singh;Ali Al-Ghouwayel;Guido Masera;Emmanuel Boutillon

  • Affiliations:

  • Lab-STICC, CNRS, UBS, Université Européenne de Bretagne, Lorient, France and VLSI Lab, Dipartimento di Elettronica, Politecnico di Torino, Torino, Italy;Lab-STICC, CNRS, UBS, Université Européenne de Bretagne, Lorient, France and VLSI Lab, Dipartimento di Elettronica, Politecnico di Torino, Torino, Italy;VLSI Lab, Dipartimento di Elettronica, Politecnico di Torino, Torino, Italy;Lab-STICC, CNRS, UBS, Université Européenne de Bretagne, Lorient, France and VLSI Lab, Dipartimento di Elettronica, Politecnico di Torino, Torino, Italy

  • Venue:
  • IEEE Communications Letters
  • Year:
  • 2009

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Abstract

In this letter, a new metric for fast and efficient performance comparison of iterative sub-optimal decoding algorithms is proposed. It is based on the estimation of a metric between the A-Posteriori Probability (APP) decoded symbol of optimal and suboptimal decoding algorithms. We apply the notion of entropy to evaluate this function. The metric is tested on data sets from the different sub optimal algorithms for the duo binary turbo codes used in WiMax(802.16e) application and a (251,502) Galois Field (26) low density parity check (LDPC) code. Experimental results show that the values of the proposed metric correlate well with the BER performance of the suboptimal implementation of the iterative decoding algorithm.