Sparse-graph codes for information reconciliation in QKD applications

This paper deals with the use of sparse-graph codes (and in particular, Low density Parity Check – LDPC – codes) for information reconciliation and pre-data sifting in Quantum Key Distribution (QKD). We model the overall channel used in QKD as the parallel of the quantum channel, where the actual quantum key is transmitted, and a public Additive White Gaussian Noise (AWGN) channel, where the parity check bits are transmitted. The metrics derived from the two channels are jointly processed at the receiver by properly combining the metrics derived from the two channels and exploiting capacity achieving soft-metric based iteratively decoded sparse-graph codes. The information derived from the iterative decoder are used to (1) perform error correction of the received qbits; (2) detect the possible presence of unauthorized eavesdroppers; (3) perform pre-data sifting. The performance of the proposed mixedsoft- metric algorithms are studied via simulations as a function of the system parameters. The core ideas of the paper are: a) employing FEC coding as opposed to two-way communication for information reconciliation, minimizing the interactions between transmitter and receiver; b) exploiting all the available information for data processing at the receiver including information available from the quantum channel; c) using convergence properties of the code to estimate QBER and presence of an eavesdropper.