Minimal characterization and provably efficient exhaustive search algorithm for elementary trapping sets of variable-regular LDPC codes
In this paper, we propose a new characterization and an efficient exhaustive search algorithm for elementary trapping sets (ETS) of variable-regular low-density parity-check (LDPC) codes. Recently, Karimi and Banihashemi proposed a characterization of ETSs, which was based on viewing an ETS as a layered superset (LSS) of a short cycle in the code's Tanner graph. Compared to the LSS-based characterization, which is based on a single LSS expansion technique, the new characterization involves two additional expansion techniques. The introduction of the new techniques mitigates two problems that LSS-based characterization/search suffers from: (1) exhaustiveness: not every ETS structure is an LSS of a cycle, (2) search efficiency: LSS-based search algorithm often requires the enumeration of cycles with length much larger than the girth of the graph, where the multiplicity of such cycles increases rapidly with their length. We prove that using the three expansion techniques, any ETS structure can be obtained starting from a simple cycle, no matter how large the size of the structure a or the number of its unsatisfied check nodes b are, i.e., the characterization is exhaustive. We also demonstrate that for the proposed characterization to exhaustively cover all the ETS structures within the (a, b) classes with a ≤ amax, b ≤ bmax, for any value of amax and bmax, the maximum length of the required cycles is minimal. The proposed characterization corresponds to a provably efficient search algorithm, significantly more efficient than the LSS-based search.
|2016 IEEE International Symposium on Information Theory, ISIT 2016|
|Organisation||Department of Systems and Computer Engineering|
Hashemi, Y. (Yoones), & Banihashemi, A. (2016). Minimal characterization and provably efficient exhaustive search algorithm for elementary trapping sets of variable-regular LDPC codes. In IEEE International Symposium on Information Theory - Proceedings (pp. 2524–2528). doi:10.1109/ISIT.2016.7541754