Free Distance Bounds for Protograph-Based Regular LDPC Convolutional Codes
David G. M. Mitchell, Ali E. Pusane, Norbert Goertz, Daniel J., Costello Jr
TL;DR
This paper establishes lower bounds on the free distance to constraint length ratio for regular LDPC convolutional codes, showing they outperform the minimum distance to block length ratio of related LDPC block codes.
Contribution
It introduces asymptotic methods to derive bounds on free distance ratios, demonstrating the superiority of convolutional codes over block codes in this metric.
Findings
Free distance to constraint length ratio exceeds that of LDPC block codes.
Asymptotic bounds are derived for regular LDPC convolutional codes.
Convolutional codes have better distance properties than block codes.
Abstract
In this paper asymptotic methods are used to form lower bounds on the free distance to constraint length ratio of several ensembles of regular, asymptotically good, protograph-based LDPC convolutional codes. In particular, we show that the free distance to constraint length ratio of the regular LDPC convolutional codes exceeds that of the minimum distance to block length ratio of the corresponding LDPC block codes.
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Taxonomy
TopicsError Correcting Code Techniques · Advanced Wireless Communication Techniques · Cooperative Communication and Network Coding