By Topic

Cross parity check convolutional codes

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
T. Fuja ; Dept. of Electr. Eng., Maryland Univ., College Park, MD, USA ; C. Heegard ; M. Blaum

A class of convolutional codes called cross parity check (CPC) codes, which are useful for the protection of data stored on magnetic tape, is described and analyzed. CPC codes are first explained geometrically; their construction is described in terms of constraining data written onto a tape in such a way that when lines of varying slope are drawn across the tape, the bits falling on those lines sum to zero modulo two. This geometric interpretation is then formalized by the construction of canonical parity check matrices and systematic generator matrices for CPC codes and by computing their constraint lengths. The distance properties of CPC codes are analyzed, and it is shown that these codes are maximum distance separable convolutional codes. In addition, examples are given of both error and erasure decoding algorithms that take advantage of the geometric regularity of CPC codes. The technique of parity check matrix reduction, which is useful for reducing the inherent decoding delay of CPC codes, is described. The technique consists of dividing each term of the parity check matrix by some polynomial and retaining only the remainder. A class of polynomials that are particularly attractive for this purpose if identified

Published in:

IEEE Transactions on Information Theory  (Volume:35 ,  Issue: 6 )