Generalized LDPC Codes With low-Complexity Decoding and Fast Convergence

We consider generalized low-density parity-check (GLDPC) codes with component codes that are duals of Cordaro–Wagner codes. Two efficient decoding algorithms are proposed: one based on Hartmann–Rudolph processing, analogous to Sum-Product decoding, and another based on evaluating two hypotheses per bit, referred to as the Min-Sum decoder. Both algorithms are derived using latent variables and a appropriate message-passing schedule. A quantized, protograph-based density evolution procedure is used to optimize GLDPC codes for Min-Sum decoding. Compared to 5G LDPC codes, the proposed GLDPC codes offer similar performance at 50 iterations and significantly better convergence and performance at 10 iterations.