Addendum to “An Efficient Algorithm to Find All Small-Size Stopping Sets of Low-Density Parity-Check Matrices”

In an earlier transactions paper, Rosnes and Ytrehus presented an efficient algorithm for determining all stopping sets of low-density parity-check (LDPC) codes, up to a specified weight, and also gave results for a number of well-known codes including the family of IEEE 802.16e LDPC codes, commonly referred to as the WiMax codes. It is the purpose of this short paper to review the algorithm for determining the initial part of the stopping set weight spectrum (which includes the codeword weight spectrum), and to provide some improvements to the algorithm. As a consequence, complete stopping set weight spectra up to weight 32 (for selected IEEE 802.16e LDPC codes) can be provided, while in previous work only stopping set weights up to 28 are reported. In the published standard for the IEEE 802.16e codes there are two methods of construction presented, depending upon the code rate and the code length. We compare the stopping sets of the resulting codes and provide complete stopping set weight spectra (up to five terms) for all IEEE 802.16e LDPC codes using both construction methods.

[1]  Naresh R. Shanbhag,et al.  High-throughput LDPC decoders , 2003, IEEE Trans. Very Large Scale Integr. Syst..

[2]  D.E. Hocevar,et al.  A reduced complexity decoder architecture via layered decoding of LDPC codes , 2004, IEEE Workshop onSignal Processing Systems, 2004. SIPS 2004..

[3]  Daniel J. Costello,et al.  LDPC block and convolutional codes based on circulant matrices , 2004, IEEE Transactions on Information Theory.

[4]  Priti Shankar,et al.  Computing the Stopping Distance of a Tanner Graph Is NP-Hard , 2007, IEEE Transactions on Information Theory.

[5]  L. Sunil Chandran,et al.  Hardness of Approximation Results for the Problem of Finding the Stopping Distance in Tanner Graphs , 2006, FSTTCS.

[6]  Rüdiger L. Urbanke,et al.  The capacity of low-density parity-check codes under message-passing decoding , 2001, IEEE Trans. Inf. Theory.

[7]  Robert G. Gallager,et al.  Low-density parity-check codes , 1962, IRE Trans. Inf. Theory.

[8]  David J. C. MacKay,et al.  Good Codes Based on Very Sparse Matrices , 1995, IMACC.

[9]  Øyvind Ytrehus,et al.  An Efficient Algorithm to Find All Small-Size Stopping Sets of Low-Density Parity-Check Matrices , 2009, IEEE Transactions on Information Theory.