  We develop a new approach for asymmetric LDPC-based information
reconciliation in order to adapt to the current channel state and achieve
better performance and scalability in practical resource-constrained QKD
systems. The new scheme combines the advantages of LDPC codes, a priori error
rate estimation, rate-adaptive and blind information reconciliation techniques.
We compare the performance of several asymmetric and symmetric error correction
schemes using real industrial QKD setup. The proposed asymmetric algorithm
achieves significantly higher throughput, providing a secret key rate very
close to the symmetric one in a wide range of error rates. Thus, our approach
turns out to be particularly efficient for applications with high key rates,
limited classical channel capacity and asymmetric computational resource
allocation.
