Characterization of Problematic Graphical Structures of LDPC Codes and the Corresponding Efficient Search Algorithms

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  • In this thesis, we study all the problematic graphical structures which play important roles in the error floor performance and error correction capability of LDPC codes. These graphical structures are:LETSs,ETSs,NETSs,stopping setsandcodewords. First, we complement LSS characterization by demonstrating how the remaining structures of LETSs can be characterized. Then, we propose a new characterization for LETSs of variable-regular LDPC codes. 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 the search efficiency problem that LSS-based characterization/search suffers from.Moreover, we generalize the proposed approach of variable-regular to irregular LDPC codes. We explain how the characterization of LETS structures in variable-regular graphs can be used to characterize the LETS structures of irregular graphs. Also, we propose a graph based approach to find all ETSs.In addition, we derive a lower bound on the size of the smallest ETSs and NETSs in variable-regular LDPC codes. The derived lower bound demonstrates that the size of the smallest possible NETS is, in general, larger than that of an ETS with the samebvalue. This provides a theoretical justification as to why NETSs are often not among the most harmful trapping sets. Moreover, we propose an efficient search algorithm to provide a list of NETSs in an interest range. Also, we derive tight lower and upper bounds on the minimum distance and stopping distance of LDPC codes. The bounds, which are established using a combination of analytical results and search techniques, are applicable to both regular and irregular LDPC codes with a wide range of rates and block lengths. The search algorithms to find codewords and stopping sets are based on the ETSs and NETSs search algorithms provided in this thesis. Extensive simulation results on several LDPC codes demonstrate the accuracy and efficiency of the proposed algorithms. In particular, the algorithms are significantly faster than the existing search algorithms in the literature.

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  • Copyright © 2017 the author(s). Theses may be used for non-commercial research, educational, or related academic purposes only. Such uses include personal study, research, scholarship, and teaching. Theses may only be shared by linking to Carleton University Institutional Repository and no part may be used without proper attribution to the author. No part may be used for commercial purposes directly or indirectly via a for-profit platform; no adaptation or derivative works are permitted without consent from the copyright owner.

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  • 2017

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