Rate-adaptive MacKay-Neal (MN) codes based on protographs are analyzed. The code construction employs an outer distribution matcher (DM) to adapt the rate of the scheme. The DM is coupled with an inner protograph-based low-density parity-check (LDPC) code. The performance achievable by the resulting code structure, that is nonlinear, is studied by means of an equivalent communication model that reduces the problem to the analysis of the inner (linear) LDPC code with transmission that takes place in parallel over the communication channel, and over a suitably defined binary symmetric channel. A density evolution analysis of protograph MN code ensembles is outlined, and it is complemented by an error floor analysis that relies on the derivation of the average input-output weight distribution of the inner LDPC code ensemble. Conditions on the shape of the normalized logarithmic asymptotic input-output weight distribution are defined, which allow discarding code ensembles with bad error floor properties during the code design phase. Examples of code designs are provided, showing how the use of a single LDPC code ensemble allows operating within 1 dB from the Shannon limit over a wide range of code rates, where the code rate is selected by tuning the DM parameters. By enabling rate flexibility with a constant blocklength, and with a fixed LDPC code as inner code, the construction provides an appealing solution for very high-throughput wireless (optical) links that employ binary-input modulations.

The variances of weight and trapping set distributions of non-binary regular low-density parity-check ensembles are derived. Using the second moment method, bounds on the probabilities that a randomly chosen code from the ensemble has its weight and trapping set distributions close to the ensemble averages are obtained.

The finite-length trapping and (elementary) absorbing set enumerators for nonbinary protograph-based LDPC code ensembles are derived. Both constrained and unconstrained edge labeling approaches are considered. The normalized logarithmic asymptotic distributions of trapping and (elementary) absorbing sets are obtained through an efficient method that requires solving a system of equations. Using these results, the asymptotic distributions of trapping and (elementary) absorbing sets are evaluated for some example nonbinary protograph-based LDPC code ensembles.

The performance of generalized low-density parity-check (GLDPC) codes under binary and ternary message passing decoding (BMP/TMP) is analyzed from a density evolution (DE) perspective. At the check nodes, two types of local decoders are considered, namely optimum a-posteriori probability (APP) soft-input soft-output decoding, and bounded distance decoding (BDD). The purpose is to shed light on the performance loss incurred by BMP and TMP decoding of GLDPC codes with respect to unquantized belief propagation (BP) decoding. A DE analysis for irregular code ensembles is developed for all the algorithms, which allows obtaining the scaling coefficients needed for the variable node operation of BMP and TMP decoders. The stability analysis for the case of bounded distance decoding at the check nodes is derived. The asymptotic DE analysis is confirmed by the finite-length simulation results. For the codes analyzed in this paper, which rely on extended Hamming component codes, the study shows that under BMP decoding, BDD at the check nodes yields almost the same performance as optimum APP check node processing, while under TMP decoding the loss incurred by the sub-optimum BDD at check nodes is within 0.7 dB, when compared with APP decoding at the check nodes.

The definitions of (elementary) trapping and (fully) absorbing sets are extended to generalized low-density parity-check (GLDPC) codes. In particular, the fully absorbing sets are stable under the bit flipping algorithm. The finite-length (elementary) trapping and (fully) absorbing set enumerators for unstructured irregular GLDPC code ensembles are derived using generating functions. An efficient method to evaluate the asymptotic trapping and (fully) absorbing set distributions is presented, which requires solving a system of equations. Using this method, the asymptotic distribution of trapping and (fully) absorbing sets are evaluated for some example GLDPC code ensembles. Experimental results show that the proposed definitions yield graph structures that are harmful for bit flipping decoders. The generating function approach is also used to derive the finite-length and asymptotic trapping and (elementary) absorbing set enumerators for non-binary irregular LDPC code ensembles.

A simple decoding algorithm, dubbed symbol message passing decoder, is studied for q-ary low-density parity-check codes over the q-ary Poisson pulse-position modulation channel. The messages in the decoder are symbols from the finite field ${\mathbb{F}_q}$. To improve performance, a second decoder with an extended message set $\left\{ {{\text{E}} \cup {\mathbb{F}_q}} \right\}$ is also investigated, where E denotes an erasure. Thresholds within 1.3 dB from the Shannon limit are obtained for low field orders.

A decoding algorithm for $q$ -ary low-density parity-check codes over the $q$ -ary symmetric channel is introduced. The exchanged messages are lists of symbols from $\mathbb{F}_{q}$ . A density evolution analysis for maximum list sizes 1 and 2 is developed. Thresholds for selected regular low-density parity-check code ensembles are computed showing gains with respect to a similar algorithm in the literature. Finite-length simulation results confirm the asymptotic analysis.

The finite-length absorbing set enumerators for non-binary protograph based low-density parity-check (LDPC) ensembles are derived. An efficient method for the evaluation of the asymptotic absorbing set distributions is presented and evaluated.

A quantized message passing decoding algorithm for low-density parity-check codes is presented. The algorithm relies on the min approximation at the check nodes, and on modelling the variable node inbound messages as observations of an extrinsic discrete memoryless channel. The performance of the algorithm is analyzed and compared to quantized min-sum decoding by means of density evolution, and almost closes the gap with the performance of the sum-product algorithm. A stability analysis is derived, which highlights the role played by degree-3 variable nodes in the stability condition. Finite-length simulation results confirm large gains predicted by the asymptotic analysis.