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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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
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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 : 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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