An Algorithm Of Multidimensional Reconciliation For Continuous-Variable Quantum Key Distribution

Information security is the subject of the information age, Cryptography technology provide a guarantee to the information security. Classical cryptography is based on computational complexity to ensure security, but with the increase in computing power, classical cryptography face enormous challenges. Quantum cryptography is made of a new cryptosystem quantum mechanics and classical cryptography, its unconditional security for information security to provide a guarantee. Quantum key distribution (Quantum Key Distribution, referred QKD) is an important part quantum cryptography. Depending on information carriers the QKD Divided into discrete variable quantum key distribution(DV-QKD) and continuous variable quantum key distribution (CV-QKD).Data coordination is the key to quantum key distribution, and its essence is the ideal classical authorized channels transmitted on the quantum channel associated with inconsistent information error correction for continuous variables and extract the same information (key) in the process, The process may be found the eavesdropper, and distilling the received key to ensure secure delivery of information.By definition, data reconciliation is a channel coding problem,Low density parity check (LDPC) is a good code close to the Shannon limit, while flexible code length and bit rate. Combining these advantages, Multidimensional reconciliation algorithm proposed LDPC codes can extend the transmission distance and shorter delay.Contents of this paper are as follows:By comparing,the SEC has higher error floor plan, shorter distance, we put forward a proposal that does not quantified the continuous variables, using the properties of Gaussian random variable square and subject to distribution to get rid of the majority of the Gaussian distribution state point close to zero and difficult dilemma binarization. Using mathematical tools to bring multidimensional continuous variables into spherical surface and study the theory to maximize the distance between apherical constellation points, Make Quantify problem into the data reconciliation algorithm which greatly reduces the computational complexity.In encoding and decoding the LDPC code, we use our laboratory’s date the double cross-linked circular list to storage matrix, and improved the distribution, while using the side information together with raw data generated by the source decoder makes the syndrome decoding more quickly and accurately. At the same time, by calculating the minimum convergence signal-to-noise ratio threshold of the algorithm is evaluated and the corresponding biggest key transmission distance of the CVQKD scheme is also estimated that confirm our algorithm is reliable.Simulation results indicate that the transmission distance between Alice and Bob is increased from 30 km to 50 km, the decoding speed is 3 times faster than the Sliced Error Correction (SEC) protocol, the raw secret rates can reach 8.61kb/s.