Transactions Papers

An Efficient New Technique for Accurate Bit Error Probability Estimation of ZJ Decoders

Khaled Letaief, Khurram Muhammad

Research output: Contribution to journalArticle

6 Citations (Scopus)

Abstract

Sequential decoding is a very powerful decoding procedure for convolutional codes which is characterized as a sequential search for the correct transmitted path through a large decision tree with random node metrics. In this paper, we present a new efficient technique for accurately estimating the bit error rates (BER's) of stack or Zigangirov-Jelinek (ZJ) sequential decoders for specific time-invariant convolutional codes. In contrast to a brute-force simulation approach, this method achieves computational efficiency by using a mean-translation importance sampling biasing method along with a set of easily checked rules which immediately eliminate the need of running the computationally intensive ZJ algorithm in a large number of simulation trials.

Original languageEnglish
Pages (from-to)2020-2027
Number of pages8
JournalIEEE Transactions on Communications
Volume43
Issue number6
DOIs
Publication statusPublished - 1995
Externally publishedYes

Fingerprint

Convolutional codes
Decoding
Importance sampling
Decision trees
Computational efficiency
Bit error rate
Error probability

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Electrical and Electronic Engineering

Cite this

Transactions Papers : An Efficient New Technique for Accurate Bit Error Probability Estimation of ZJ Decoders. / Letaief, Khaled; Muhammad, Khurram.

In: IEEE Transactions on Communications, Vol. 43, No. 6, 1995, p. 2020-2027.

Research output: Contribution to journalArticle

@article{a0d7d46b0f824600b500bc7b6be41a44,
title = "Transactions Papers: An Efficient New Technique for Accurate Bit Error Probability Estimation of ZJ Decoders",
abstract = "Sequential decoding is a very powerful decoding procedure for convolutional codes which is characterized as a sequential search for the correct transmitted path through a large decision tree with random node metrics. In this paper, we present a new efficient technique for accurately estimating the bit error rates (BER's) of stack or Zigangirov-Jelinek (ZJ) sequential decoders for specific time-invariant convolutional codes. In contrast to a brute-force simulation approach, this method achieves computational efficiency by using a mean-translation importance sampling biasing method along with a set of easily checked rules which immediately eliminate the need of running the computationally intensive ZJ algorithm in a large number of simulation trials.",
author = "Khaled Letaief and Khurram Muhammad",
year = "1995",
doi = "10.1109/26.387442",
language = "English",
volume = "43",
pages = "2020--2027",
journal = "IEEE Transactions on Communications",
issn = "0096-1965",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
number = "6",

}

TY - JOUR

T1 - Transactions Papers

T2 - An Efficient New Technique for Accurate Bit Error Probability Estimation of ZJ Decoders

AU - Letaief, Khaled

AU - Muhammad, Khurram

PY - 1995

Y1 - 1995

N2 - Sequential decoding is a very powerful decoding procedure for convolutional codes which is characterized as a sequential search for the correct transmitted path through a large decision tree with random node metrics. In this paper, we present a new efficient technique for accurately estimating the bit error rates (BER's) of stack or Zigangirov-Jelinek (ZJ) sequential decoders for specific time-invariant convolutional codes. In contrast to a brute-force simulation approach, this method achieves computational efficiency by using a mean-translation importance sampling biasing method along with a set of easily checked rules which immediately eliminate the need of running the computationally intensive ZJ algorithm in a large number of simulation trials.

AB - Sequential decoding is a very powerful decoding procedure for convolutional codes which is characterized as a sequential search for the correct transmitted path through a large decision tree with random node metrics. In this paper, we present a new efficient technique for accurately estimating the bit error rates (BER's) of stack or Zigangirov-Jelinek (ZJ) sequential decoders for specific time-invariant convolutional codes. In contrast to a brute-force simulation approach, this method achieves computational efficiency by using a mean-translation importance sampling biasing method along with a set of easily checked rules which immediately eliminate the need of running the computationally intensive ZJ algorithm in a large number of simulation trials.

UR - http://www.scopus.com/inward/record.url?scp=0029323472&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0029323472&partnerID=8YFLogxK

U2 - 10.1109/26.387442

DO - 10.1109/26.387442

M3 - Article

VL - 43

SP - 2020

EP - 2027

JO - IEEE Transactions on Communications

JF - IEEE Transactions on Communications

SN - 0096-1965

IS - 6

ER -