Memory-Assisted Quantized LDPC Decoding

We enhance coarsely quantized LDPC decoding by reusing computed check node messages from previous iterations. Typically, variable and check nodes generate and replace old messages in every iteration. We show that, under coarse quantization, discarding old messages involves a significant loss of mutual information. The loss is avoided with additional memory, improving performance up to 0.36 dB. We propose a modified information bottleneck algorithm to design node operations taking messages from the previous iteration(s) into account as side information. Finally, we reveal a 2-bit row-layered decoder that can operate within 0.25 dB w.r.t. 32-bit belief propagation.