  We propose a quantized decoding algorithm for low- density parity-check codes
where the variable node update rule of the standard min-sum algorithm is
replaced with a look-up table (LUT) that is designed using an
information-theoretic criterion. We show that even with message resolutions as
low as 3 bits, the proposed algorithm can achieve better error rates than a
floating-point min-sum decoder. Moreover, we study in detail the effect of
different decoder design parameters, like the design SNR and the LUT tree
structure on the performance of our decoder, and we propose some complexity
reduction techniques, such as LUT re-use and message alphabet downsizing.
