The below 3 papers are on non-binary LDPC code and were published at the ISIT conference. We may look into the details for some new ideas to be included in the proposal.
1.
Performance of ML Decoding for Ensembles of Binary and Nonbinary Regular LDPC Codes of Finite Lengths#^https://ieeexplore.ieee.org/abstract/document/8006637This paper estimates the ML decoding error probability for the AWGN channel by using average weight enumerators for both binary random LDPC codes and binary images of random nonbinary LDPC codes. The new upper bounds are obtained on the ML decoding performance, based on the precise coefficients of the average weight spectra. However, they have concluded that ML decoding performance should not be used as a target for searching for good iteratively decodable codes.
2.
Construction of Rate (n - 1)/n Non-Binary LDPC Convolutional Codes via Difference Triangle Sets#^https://ieeexplore.ieee.org/abstract/document/9174510This paper analyzed the structure of different triangle sets to construct non-binary LDPC convolutional codes whose parity check matrices are free from 4-cycles and 6-cycles. They have given the construction of rate (n - 1)/n convolutional codes over non-binary fields, generalizing a construction from Robinson and Bernstein, using difference triangle sets.
3.
A Class of Non-Binary Doubly-Generalized LDPC codes for Moderate and High Code Rates#^https://ieeexplore.ieee.org/abstract/document/9518035They proposed a small fraction of single parity-check codes at the side of the variable node. They have claimed that (together with the use of extended alphabets) the existence of such a fraction has been shown to improve the asymptotic decoding threshold, without harming the minimum distance.