Performance analysis of linear codes under maximum-likelihood decoding: a tutorial
Communications and Information Theory
Sharp bounds for optimal decoding of low-density parity-check codes
IEEE Transactions on Information Theory
On universal properties of capacity-approaching LDPC code ensembles
IEEE Transactions on Information Theory
Allerton'09 Proceedings of the 47th annual Allerton conference on Communication, control, and computing
Adaptive coding and modulation for hybrid FSO/RF systems
Asilomar'09 Proceedings of the 43rd Asilomar conference on Signals, systems and computers
LDPC code design considerations for non-uniform channels
IEEE Transactions on Communications
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A variety of communication scenarios can be modeled by a set of parallel channels. Upper bounds on the achievable rates under maximum-likelihood (ML) decoding, and lower bounds on the decoding complexity per iteration of ensembles of low-density parity-check (LDPC) codes are presented. The communication of these codes is assumed to take place over statistically independent parallel channels where the component channels are memoryless, binary-input, and output-symmetric. The bounds are applied to ensembles of punctured LDPC codes where the puncturing patterns are either random or possess some structure. Our discussion is concluded by a diagram showing interconnections between the new theorems and some previously reported results