The invention discloses a layered LDPC (
Low Density Parity Check Code) decoding method based on syndrome feedback self-adaption, and aims to solve the problem of poor decoding performance caused by fixed correction factors and poor adaptability to different check matrixes and channel conditions in the existing
LDPC decoding algorithm. The method comprises the following steps of: firstly, dividing rows of a check matrix into a plurality of independent
layers by adopting a hierarchical scheduling architecture so as to accelerate propagation and convergence of decoding information; secondly, in each
iteration process of hierarchical decoding, a self-adaptive
mechanism based on syndrome feedback is used, and a core offset factor beta in an offset minimum sum
algorithm is adjusted in real time; the mechanism intelligently increases or decreases the offset factor by diagnosing the current decoding state (i.e., the number of unsatisfied check equations) to help the decoding process jump out of
local optimum and stably converge. A
simulation result shows that compared with a traditional offset minimum sum
algorithm, the decoding performance is effectively improved and the
bit error rate is reduced on the premise that the complexity is not obviously increased, and particularly, the performance
gain is obvious in a medium-high
signal-to-
noise ratio region, and the robustness is higher.