Characterization and Efficient Search of Non-Elementary Trapping Sets of LDPC Codes With Applications to Stopping Sets

In this paper, we propose a characterization for non-elementary trapping sets (NETSs) of low-density parity-check (LDPC) codes. The characterization is based on viewing an NETS as a hierarchy of embedded graphs starting from an ETS. The characterization corresponds to an efficient search algorithm that under certain conditions is exhaustive. As an application of the proposed characterization/search, we obtain lower and upper bounds on the stopping distance <inline-formula> <tex-math notation="LaTeX">$s_{\min }$ </tex-math></inline-formula> of LDPC codes. We examine a large number of regular and irregular LDPC codes and demonstrate the efficiency and versatility of our technique in finding lower and upper bounds on, and in many cases the exact value of, <inline-formula> <tex-math notation="LaTeX">$s_{\min }$ </tex-math></inline-formula>. Finding <inline-formula> <tex-math notation="LaTeX">$s_{\min }$ </tex-math></inline-formula>, or establishing search-based lower or upper bounds, for many of the examined codes are out of the reach of any existing algorithm. For a constant degree distribution and range of search, the worst case computational complexity of the proposed search algorithms for finding NETSs and stopping sets is linear in the code’s block length <inline-formula> <tex-math notation="LaTeX">$n$ </tex-math></inline-formula>. The average search complexity for stopping sets, however, is constant in <inline-formula> <tex-math notation="LaTeX">$n$ </tex-math></inline-formula>, if the simple cycles required as input to the search algorithm are available.

[1]  Paul H. Siegel,et al.  Bounds on the Minimum Distance of Punctured Quasi-Cyclic LDPC Codes , 2012, IEEE Transactions on Information Theory.

[2]  Thomas J. Richardson,et al.  Error Floors of LDPC Codes , 2003 .

[3]  Amir H. Banihashemi,et al.  On the Tanner Graph Cycle Distribution of Random LDPC, Random Protograph-Based LDPC, and Random Quasi-Cyclic LDPC Code Ensembles , 2017, IEEE Transactions on Information Theory.

[4]  Jacques Stern,et al.  A method for finding codewords of small weight , 1989, Coding Theory and Applications.

[5]  Marcel Ambroze,et al.  Addendum to “An Efficient Algorithm to Find All Small-Size Stopping Sets of Low-Density Parity-Check Matrices” , 2012, IEEE Transactions on Information Theory.

[6]  R. M. Tanner,et al.  A Class of Group-Structured LDPC Codes , 2001 .

[7]  Evangelos Eleftheriou,et al.  Regular and irregular progressive edge-growth tanner graphs , 2005, IEEE Transactions on Information Theory.

[8]  Gerd Richter,et al.  Finding Small Stopping Sets in the Tanner Graphs of LDPC Codes , 2006 .

[9]  Amir H. Banihashemi,et al.  On Characterization of Elementary Trapping Sets of Variable-Regular LDPC Codes , 2014, IEEE Trans. Inf. Theory.

[10]  A. Orlitsky,et al.  Stopping sets and the girth of Tanner graphs , 2002, Proceedings IEEE International Symposium on Information Theory,.

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

[12]  Amir H. Banihashemi,et al.  Symmetrical Constructions for Regular Girth-8 QC-LDPC Codes , 2017, IEEE Transactions on Communications.

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

[14]  Amir H. Banihashemi,et al.  On Characterization and Efficient Exhaustive Search of Elementary Trapping Sets of Variable-Regular LDPC Codes , 2015, IEEE Communications Letters.

[15]  Amir H. Banihashemi,et al.  Efficient Search of Girth-Optimal QC-LDPC Codes , 2016, IEEE Transactions on Information Theory.

[16]  Marcel Ambroze,et al.  On the Minimum/Stopping Distance of Array Low-Density Parity-Check Codes , 2012, IEEE Transactions on Information Theory.

[17]  Amir H. Banihashemi,et al.  Characterization of Elementary Trapping Sets in Irregular LDPC Codes and the Corresponding Efficient Exhaustive Search Algorithms , 2018, IEEE Transactions on Information Theory.

[18]  Evangelos S. Eleftheriou,et al.  A Probabilistic Subspace Approach to the Minimal Stopping Set Problem , 2006 .

[19]  Masakatu Morii,et al.  On the probabilistic computation algorithm for the minimum-size stopping sets of LDPC codes , 2008, 2008 IEEE International Symposium on Information Theory.

[20]  Amir H. Banihashemi,et al.  Lower Bounds on the Size of Smallest Elementary and Non-Elementary Trapping Sets in Variable-Regular LDPC Codes , 2017, IEEE Communications Letters.