Tree consistency and bounds on the performance of the max-product algorithm and its generalizations
Statistics and Computing
Graphical Models, Exponential Families, and Variational Inference
Foundations and Trends® in Machine Learning
Instanton-based techniques for analysis and reduction of error floors of LDPC codes
IEEE Journal on Selected Areas in Communications - Special issue on capaciyy approaching codes
Decreasing error floor in LDPC codes by parity-check matrix extensions
ISIT'09 Proceedings of the 2009 IEEE international conference on Symposium on Information Theory - Volume 1
On the dynamics of the error floor behavior in (regular) LDPC codes
IEEE Transactions on Information Theory
Journal of Electrical and Computer Engineering - Special issue on iterative signal processing in communications
Message-passing algorithms for quadratic minimization
The Journal of Machine Learning Research
| Hi-index | 754.90 |
By tracing the flow of computations in the iterative decoders for low-density parity-check codes, we formulate a signal-space view for a finite number of iterations in a finite-length code. On a Gaussian channel, maximum a posteriori (MAP) codeword decoding (or “maximum-likelihood decoding”) decodes to the codeword signal that is closest to the channel output in Euclidean distance. In contrast, we show that iterative decoding decodes to the “pseudosignal” that has highest correlation with the channel output. The set of pseudosignals corresponds to “pseudocodewords”, only a vanishingly small number of which correspond to codewords. We show that some pseudocodewords cause decoding errors, but that there are also pseudocodewords that frequently correct the deleterious effects of other pseudocodewords