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On the complexity of bounded distance decoding for the AWGN channel

Anderson, John B LU (2002) In IEEE Transactions on Information Theory 48(5). p.1046-1060
Abstract
Earlier work has derived the storage complexity of the bounded distance decoder (BDD) for binary-channel convolutional codes. We extend this work to the Gaussian noise channel and to partial-response codes. We show that the storage requirement similar to(2(1-R) - 1)(-t) paths for rate-R convolutional codes over the binary channel becomes similar to2(2Rt) over the Gaussian channel, where the decoder must correct t errors. Thus, convolutional coding over the Gaussian channel is not only 3 dB more energy efficient, but its decoding is simpler as well. Next, we estimate the path storage for partial-response codes, i.e., real-number convolutional codes, over the Gaussian channel. The growth rate depends primarily on the bandwidth of the code. A... (More)
Earlier work has derived the storage complexity of the bounded distance decoder (BDD) for binary-channel convolutional codes. We extend this work to the Gaussian noise channel and to partial-response codes. We show that the storage requirement similar to(2(1-R) - 1)(-t) paths for rate-R convolutional codes over the binary channel becomes similar to2(2Rt) over the Gaussian channel, where the decoder must correct t errors. Thus, convolutional coding over the Gaussian channel is not only 3 dB more energy efficient, but its decoding is simpler as well. Next, we estimate the path storage for partial-response codes, i.e., real-number convolutional codes, over the Gaussian channel. The growth rate depends primarily on the bandwidth of the code. A new optimization procedure is devised to measure the maximum storage requirement in Gaussian noise for these two code types. An analysis based on difference equations predicts the asymptotic storage growth for partial response codes. (Less)
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author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
decoding complexity, intersymbol, partial response coding, interference reduction, convolutional coding, decoding
in
IEEE Transactions on Information Theory
volume
48
issue
5
pages
1046 - 1060
publisher
IEEE--Institute of Electrical and Electronics Engineers Inc.
external identifiers
  • wos:000174970900004
  • scopus:0036566745
ISSN
0018-9448
DOI
10.1109/18.995541
project
Informations- och kommunikationsteori: Kodningsteori
language
English
LU publication?
yes
id
e236ce25-7e78-4f7b-8bd7-bb787dc5bd4b (old id 340322)
date added to LUP
2007-08-06 15:58:04
date last changed
2017-01-01 06:44:20
@article{e236ce25-7e78-4f7b-8bd7-bb787dc5bd4b,
  abstract     = {Earlier work has derived the storage complexity of the bounded distance decoder (BDD) for binary-channel convolutional codes. We extend this work to the Gaussian noise channel and to partial-response codes. We show that the storage requirement similar to(2(1-R) - 1)(-t) paths for rate-R convolutional codes over the binary channel becomes similar to2(2Rt) over the Gaussian channel, where the decoder must correct t errors. Thus, convolutional coding over the Gaussian channel is not only 3 dB more energy efficient, but its decoding is simpler as well. Next, we estimate the path storage for partial-response codes, i.e., real-number convolutional codes, over the Gaussian channel. The growth rate depends primarily on the bandwidth of the code. A new optimization procedure is devised to measure the maximum storage requirement in Gaussian noise for these two code types. An analysis based on difference equations predicts the asymptotic storage growth for partial response codes.},
  author       = {Anderson, John B},
  issn         = {0018-9448},
  keyword      = {decoding complexity,intersymbol,partial response coding,interference reduction,convolutional coding,decoding},
  language     = {eng},
  number       = {5},
  pages        = {1046--1060},
  publisher    = {IEEE--Institute of Electrical and Electronics Engineers Inc.},
  series       = {IEEE Transactions on Information Theory},
  title        = {On the complexity of bounded distance decoding for the AWGN channel},
  url          = {http://dx.doi.org/10.1109/18.995541},
  volume       = {48},
  year         = {2002},
}