On the stopping distance and the stopping redundancy of codes

It is now well known that the performance of a linear code Copf under iterative decoding on a binary erasure channel (and other channels) is determined by the size of the smallest stopping set in the Tanner graph for Copf. Several recent papers refer to this parameter as the stopping distance s of Copf. This is somewhat of a misnomer since the size of the smallest stopping set in the Tanner graph for Copf depends on the corresponding choice of a parity-check matrix. It is easy to see that s les d, where d is the minimum Hamming distance of Copf, and we show that it is always possible to choose a parity-check matrix for Copf (with sufficiently many dependent rows) such that s = d. We thus introduce a new parameter, termed the stopping redundancy of Copf, defined as the minimum number of rows in a parity-check matrix H for Copf such that the corresponding stopping distance s(H) attains its largest possible value, namely s(H) = d. We then derive general bounds on the stopping redundancy of linear codes. We also examine several simple ways of constructing codes from other codes, and study the effect of these constructions on the stopping redundancy. Specifically, for the family of binary Reed-Muller codes (of all orders), we prove that their stopping redundancy is at most a constant times their conventional redundancy. We show that the stopping redundancies of the binary and ternary extended Golay codes are at most 34 and 22, respectively. Finally, we provide upper and lower bounds on the stopping redundancy of MDS codes

[1]  A. Vardy,et al.  Stopping sets in codes from designs , 2003, IEEE International Symposium on Information Theory, 2003. Proceedings..

[2]  F. MacWilliams,et al.  The Theory of Error-Correcting Codes , 1977 .

[3]  Alon Orlitsky,et al.  Stopping set distribution of LDPC code ensembles , 2003, IEEE Transactions on Information Theory.

[4]  N. J. A. Sloane,et al.  Good self dual codes exist , 1972, Discret. Math..

[5]  Noga Alon,et al.  Locally Thin Set Families , 2000, Comb. Probab. Comput..

[6]  G. Kuperberg,et al.  New constructions for covering designs , 1995, math/9502238.

[7]  Paul H. Siegel,et al.  Improved Upper Bounds on Stopping Redundancy , 2005, IEEE Transactions on Information Theory.

[8]  Jon Feldman,et al.  Decoding error-correcting codes via linear programming , 2003 .

[9]  N. J. A. Sloane,et al.  Sphere Packings, Lattices and Groups , 1987, Grundlehren der mathematischen Wissenschaften.

[10]  Noga Alon,et al.  String Quartets in Binary , 2000, Combinatorics, Probability and Computing.

[11]  Alexander Sidorenko,et al.  Upper Bounds for Turán Numbers , 1997, J. Comb. Theory, Ser. A.

[12]  Alexander Vardy,et al.  On the effect of parity-check weights in iterative decoding , 2004, International Symposium onInformation Theory, 2004. ISIT 2004. Proceedings..

[13]  N. J. A. Sloane,et al.  Orbit and coset analysis of the Golay and related codes , 1990, IEEE Trans. Inf. Theory.

[14]  Emre Telatar,et al.  Finite-length analysis of low-density parity-check codes on the binary erasure channel , 2002, IEEE Trans. Inf. Theory.

[15]  N. J. A. Sloane,et al.  Lower bounds for constant weight codes , 1980, IEEE Trans. Inf. Theory.

[16]  Joel H. Spencer,et al.  Asymptotically Optimal Covering Designs , 1995, J. Comb. Theory, Ser. A.

[17]  Tuvi Etzion On the Stopping Redundancy of Reed-Muller Codes , 2006, IEEE Trans. Inf. Theory.

[18]  A. Robert Calderbank,et al.  Minimal tail-biting trellises: The Golay code and more , 1999, IEEE Trans. Inf. Theory.