  In this paper, we propose an enhanced quasi-maximum likelihood (EQML) decoder
for LDPC codes with short block lengths. After the failure of the conventional
belief propagation (BP) decoding, the proposed EQML decoder selects unreliable
variable nodes (VNs) and saturates their associated channel output values to
generate a list of decoder input sequences. Each decoder input sequence in the
list is then decoded by the conventional BP decoder to obtain the most likely
codeword. To improve the accuracy of selecting unreliable VNs, we propose an
edge-wise selection method based on the sign fluctuation of VNs' extrinsic
messages. A partial pruning stopping (PPS) rule is also presented to reduce the
decoding latency. Simulation results show that the proposed EQML decoder
outperforms the conventional BP decoder and the augmented BP decoder for short
LDPC codes. It even approaches the performance of ML decoding within 0.3 dB in
terms of frame error rate. In addition, the proposed PPS rule achieves a lower
decoding latency compared to the list decoding stopping rule.
