Minimality for puncturing convolutional codes. Fragouli, C., Komninakis, C., & Wesel, R. D. ICC 2001, Helsinki, Finland, June, vol. 1:pages 300–304, 2001. abstract bibtex This paper investigates encoders optimization for the Hamming weight after periodic puncturing, and discusses minimality issues that may affect the performance of the punctured encoders. Periodically puncturing a minimal encoder produces a higher rate encoder that may or may not be minimal. If it is not minimal, it may have a zero-output loop and it may be catastrophic. A code search can use a fast algorithm to determine whether an encoder's state diagram has a zero-output loop under periodic symbol puncturing, and a proposed method to assess the performance of codes with a zero-output loop that are not catastrophic. As an example, the paper optimizes rate-1/4 unpunctured codes for Hamming weight under both bit-wise and symbol-wise periodic puncturing. Code tables and simulation results are included.
@article{fragouli_minimality_2001,
abstract = {This paper investigates encoders optimization for the Hamming weight after periodic puncturing, and discusses minimality issues that may affect the performance of the punctured encoders. Periodically puncturing a minimal encoder produces a higher rate encoder that may or may not be minimal. If it is not minimal, it may have a zero-output loop and it may be catastrophic. A code search can use a fast algorithm to determine whether an encoder's state diagram has a zero-output loop under periodic symbol puncturing, and a proposed method to assess the performance of codes with a zero-output loop that are not catastrophic. As an example, the paper optimizes rate-1/4 unpunctured codes for Hamming weight under both bit-wise and symbol-wise periodic puncturing. Code tables and simulation results are included.},
type={4},
author = {Fragouli, C. and Komninakis, C. and Wesel, R. D.},
journal = {ICC 2001, Helsinki, Finland, June},
pages = {pages 300--304},
tags = {channel_coding},
title = {Minimality for puncturing convolutional codes},
volume = {vol. 1},
year = {2001}
}
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