On the complexity of bounded distance decoding for the AWGN channel
(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)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/340322
- author
- Anderson, John B LU
- organization
- publishing date
- 2002
- 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
- 2016-04-01 15:40:12
- date last changed
- 2022-01-28 06:32:55
@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}}, keywords = {{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}}, doi = {{10.1109/18.995541}}, volume = {{48}}, year = {{2002}}, }