On the complexity of bounded distance decoding for the AWGN channel

Summary, in English

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: John B Anderson
• Department/s: Department of Electrical and Information Technology
• Publishing year: 2002
• Language: English
• Pages: 1046-1060
• Publication/Series: IEEE Transactions on Information Theory
• Volume: 48
• Issue: 5
• Links: http://dx.doi.org/10.1109/18.995541
• Document type: Journal article
• Publisher: IEEE - Institute of Electrical and Electronics Engineers Inc.
• Topic: Electrical Engineering, Electronic Engineering, Information Engineering
• Keywords: decoding complexity; intersymbol; partial response coding; interference reduction; convolutional coding; decoding
• Status: Published
• Project: Informations- och kommunikationsteori: Kodningsteori
• Research group: Informations- och kommunikationsteori
• ISBN/ISSN/Other: ISSN: 0018-9448