Decoding metrics and their applications in VLSI turbo decoders

Zhongfeng Wang, Keshnb K. Parhi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

8 Scopus citations

Abstract

In this paper, a set of variables which can be easily computed in the course of iterative decoding of turbo decoders called decoding metrics (DMs) are introduced. According to the measured DMs after each iteration, a lot of information other than signal-to-noise ratio (SNR) in the received bits, such as how good/bad the current block is and how close the current iteration of decoding is to convergence, can be obtained. Detailed discussions are provided regarding why these variables are chosen. Based on the measured DMs after the first iteration, an approximate SNR-related variable Lc can be obtained for MAP-based turbo decoders. Simulation results show that there is almost no performance degradation if approximated Lc values are used instead of exact values. It is also shown that adaptive decoding using DMs is more efficient than existing methods both in terms of hardware and latency. Other applications of DMs are pointed out at last.

Original languageEnglish (US)
Title of host publicationDesign and Implementation of Signal Processing SystemNeural Networks for Signal Processing Signal Processing EducationOther Emerging Applications of Signal ProcessingSpecial Sessions
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3370-3373
Number of pages4
ISBN (Electronic)0780362934
DOIs
StatePublished - 2000
Event25th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2000 - Istanbul, Turkey
Duration: Jun 5 2000Jun 9 2000

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume6
ISSN (Print)1520-6149

Other

Other25th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2000
CountryTurkey
CityIstanbul
Period6/5/006/9/00

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