Mutual Information-Maximizing Quantized Belief Propagation Decoding of LDPC Codes
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A severe problem for mutual information-maximizing lookup table (MIM-LUT) decoding of low-density parity-check (LDPC) code is the high memory cost for using large tables, while decomposing large tables to small tables deteriorates decoding error performance. In this paper, we propose a method, called mutual information-maximizing quantized belief propagation (MIM-QBP) decoding, to remove the lookup tables used for MIM-LUT decoding. Our method leads to a very practical decoder, namely MIM-QBP decoder, which can be implemented based only on simple mappings and fixed-point additions. We further present how to practically and systematically design the MIM-QBP decoder for both regular and irregular LDPC codes. Simulation results show that the MIM-QBP decoder can always considerably outperform the state-of-the-art MIM-LUT decoder. Furthermore, the MIM-QBP decoder with only 3 bits per message can outperform the floating-point belief propagation (BP) decoder at high signal-to-noise ratio (SNR) region when testing on high rate codes with a maximum of 10--30 iterations.
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