A Novel Method for Blind Identification of a (n, n-1, m) Convolutional Code - Volume 7 Number 2 (Jun. 2018) - IJFCC
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General Information
    • ISSN: 2010-3751
    • Frequency: Bimonthly (2012-2016); Quarterly (Since 2017)
    • DOI: 10.18178/IJFCC
    • Editor-in-Chief: Prof. Mohamed Othman
    • Executive Editor: Ms. Cherry L. Chan
    • Abstracting/ Indexing: Google Scholar,  Crossref, Electronic Journals LibraryEI (INSPEC, IET), etc.
    • E-mail:  ijfcc@ejournal.net 
Editor-in-chief
Prof. Mohamed Othman
Department of Communication Technology and Network Universiti Putra Malaysia, Malaysia
It is my honor to be the editor-in-chief of IJFCC. The journal publishes good papers in the field of future computer and communication. Hopefully, IJFCC will become a recognized journal among the readers in the filed of future computer and communication.
IJFCC 2018 Vol.7(2): 46-50 ISSN: 2010-3751
DOI: 10.18178/ijfcc.2018.7.2.519

A Novel Method for Blind Identification of a (n, n-1, m) Convolutional Code

Shu Nan Han and Min Zhang
Abstract—The existing methods for identification of a ( ,,) 儃1 n nmconvolutional code are not applicable in the cases of high bit error rates or need a large amount of computation. To overcome the limitations, a novel blind identification method is proposed. First, based on the parity check equation set, the parity check vector of a convolutional code is estimated by using the proposed recursive algorithm. Second, due to the orthogonality between the parity check matrix and the generator matrix, a set of polynomial generator bases are obtained. Finally, the canonical generator matrix is reconstructed by using the polynomial generator bases. Experimental results show the method is effective. The method has high robustness to bit errors. It does not need to search for the parity check vector exhaustively, and therefore its computational complexity is much lower than that of the existing method.

Index Terms—Convolutional code, blind identification, parity check matrix, robustness.

The authors are with the National University of Defense Technology, Hefei, China (e-mail: hsnnong@163.com).

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Cite: Shu Nan Han and Min Zhang, "A Novel Method for Blind Identification of a (n, n-1, m) Convolutional Code," International Journal of Future Computer and Communication vol. 7, no.2, pp. 46-50, 2018.

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