A new class of parallel data convolutional codes

Xiang, Wei and Pietrobon, Steven S. (2005) A new class of parallel data convolutional codes. In: AusCTW 2005: 6th Australian Communications Theory Workshop, 2-4 Feb 2005, Brisbane, Australia.

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Abstract

We propose a new class of parallel data convolutional codes (PDCCs) in this paper. The PDCC encoders inputs are composed of an original block of data and its interleaved version. A novel single self-iterative soft-in/soft-out a posteriori probability (APP) decoder structure is proposed for the decoding of the PDCCs. Simulation results are presented to compare the performance of PDCCs.


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Item Type: Conference or Workshop Item (Commonwealth Reporting Category E) (Paper)
Refereed: Yes
Item Status: Live Archive
Additional Information: This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of the products or services of the University of Southern Queensland. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.
Depositing User: epEditor USQ
Faculty / Department / School: Historic - Faculty of Engineering and Surveying - Department of Electrical, Electronic and Computer Engineering
Date Deposited: 11 Oct 2007 00:25
Last Modified: 02 Jul 2013 22:33
Uncontrolled Keywords: parallel data convolutional codes (PDCCs) self-iterative, a posteriori probability (APP)
Fields of Research (FOR2008): 09 Engineering > 0906 Electrical and Electronic Engineering > 090602 Control Systems, Robotics and Automation
09 Engineering > 0906 Electrical and Electronic Engineering > 090609 Signal Processing
URI: http://eprints.usq.edu.au/id/eprint/591

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