A greedy relocation framework builds multi-dimensional spatially-coupled LDPC codes with fewer short cycles and substantially better bit-error-rate than comparable one-dimensional codes.
Efficient Search and Elimination of Harmful Objects in Optimized QC SC-LDPC Codes
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abstract
The error correction performance of low-density parity-check (LDPC) codes under iterative message-passing decoding is degraded by the presence of certain harmful objects existing in their Tanner graph representation. Depending on the context, such harmful objects are known as stopping sets, trapping sets, absorbing sets, or pseudocodewords. In this paper, we propose a general procedure based on edge spreading that enables the design of quasi-cyclic (QC) spatially coupled low-density parity-check codes (SC-LDPCCs) that are derived from QC-LDPC block codes and possess a significantly reduced multiplicity of harmful objects with respect to the original QC-LDPC block code. This procedure relies on a novel algorithm that greedily spans the search space of potential candidates to reduce the multiplicity of the target harmful object(s) in the Tanner graph. The effectiveness of the method we propose is validated via examples and numerical computer simulations.
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2019 1verdicts
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Multi-Dimensional Spatially-Coupled Code Design: Enhancing the Cycle Properties
A greedy relocation framework builds multi-dimensional spatially-coupled LDPC codes with fewer short cycles and substantially better bit-error-rate than comparable one-dimensional codes.