Low-Complexity Linear Programming Based Decoding of Quantum LDPC codes
CoRR(2023)
摘要
This paper proposes two approaches for reducing the impact of the error floor
phenomenon when decoding quantum low-density parity-check codes with belief
propagation based algorithms. First, a low-complexity syndrome-based linear
programming (SB-LP) decoding algorithm is proposed, and second, the proposed
SB-LP is applied as a post-processing step after syndrome-based min-sum (SB-MS)
decoding. For the latter case, a new early stopping criterion is introduced to
decide when to activate the SB-LP algorithm, avoiding executing a predefined
maximum number of iterations for the SB-MS decoder. Simulation results show,
for a sample hypergraph code, that the proposed decoder can lower the error
floor by two to three orders of magnitude compared to SB-MS for the same total
number of decoding iterations.
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