This paper tightens previous information combining bounds on the performance of iterative decoding of binary low-density parity-check (LDPC) codes over binary-input symmetric-output channels by tracking the probability of erroneous bit in conjunction with mutual information. Evaluation of the new bounds as well as of other known bounds on different LDPC ensembles demonstrates sensitivity of the finite dimensional iterative bounds to lambda2, the fraction of edges connected to degree 2 variable nodes

We present a setting for decoding of low-density parity-check (LDPC) codes jointly with channel estimation, which is suitable for transmission over memoryless compound channels. We show that the performance of the combined scheme can be rigorously evaluated by means of density evolution, and focus on density evolution as a tool for designing a channel estimator that matches not only to the channel, but also to the LDPC ensemble, as well. The utility of the concept is exemplified for a compound binary symmetric channel and an unknown phase additive white Gaussian channel.

Iterative Decoding of Low-Density Parity-Check Codes Over Compound Channels We present a setting for decoding of low-density parity-check (LDPC) codes jointly with channel estimation, suitable for transmission over memoryless compound channels. We show that the performance of the combined scheme can be rigorously evaluated by means of density evolution, and focus on density evolution as a tool for designing a channel estimator that matches not only to the channel, but also to the LDPC ensemble, as well. The utility of the concept is exemplified for a compound binary symmetric channel and an unknown-phase additive white Gaussian channel.

Extreme densities for information combining are found for two important channel models: the binary-input symmetric parallel broadcast channel and the parity-constrained-input symmetric parallel channels. Following, upper and lower mutual information thresholds are stated for per-bit maximum a posteriori probability (MAP) decoding and low-density parity-check (LDPC) code ensembles.