Efficient encoding of low-density parity-check codes

By T. Richardson, Rüdiger L. Urbanke. IEEE Transactions on Information Theory, 2001

1,122 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/1ab6692caf7cc6b25e27fb59531c3a193c80d032

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In Computer Networks and Communications

In Electrical and Electronic Engineering

Citations in the corpus

Design of efficiently encodable moderate-length high-rate irregular LDPC codes (2004, background): “Thus, in order for to correspond to a cycle-free part of the graph, we must have .”
LDPC block and convolutional codes based on circulant matrices (2004, methodology): “…described (i.e., one for which either or , but the rank drop in the parity-check matrix is larger than one, thus violating the condition for Lemma 3.1), then by a procedure akin to the one described in [24], the parity-check matrix can be reduced to a form where graph-based encoding almost works.”
Progressive edge-growth Tanner graphs (2001, positive): “SPA on a Tanner graph has been shown to be independent of block length , but the encoding complexity generally scales as , an issue addressed, e.g., in [10, 12, 13 , 15].”
Design of capacity-approaching irregular low-density parity-check codes (2001, background): “An alternative solution for practical purposes, which does not require cascades, is presented in [4].”
Regular and irregular progressive edge-growth tanner graphs (2005, background): “Several publications address this issue, with the aim of obtaining linear-time-encoding complexity, see for example [44]–[49].”
Sparse-graph codes for quantum error correction (2003, methodology): “For all four constructions B, U, N, and M, another option would be to try the methods of Richardson and Urbanke (2001b) for lowering the complexity of encoding.”
Efficient encoding of quasi-cyclic low-density parity-check codes (2005, background): “This is a substantial improvement over the quadratic complexity involved in general type of LDPC codes [ 7 ].”
Raptor codes on binary memoryless symmetric channels (2006, methodology): “Others, such as the method described in [12], stay faithful to LDPC codes and design efficient encoding algorithms that often run in linear time.”
Finite-length analysis of low-density parity-check codes on the binary erasure channel (2002, neutral): “This combinatorial characterization was originally proposed in [12] in the context of the efficient encodingof LDPC codes.”