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Ceshi jishu xuebao

The Optimized Algorithm for Data Reconciliation Based on Particle Swarm Optimization

Sun Y

Published Jan 1, 2015• 5 citations
OpenAlex

Abstract

According to the basic principle of the density evolution for the irregular low-density paritycheck(LDPC)codes,the parity check matrix His optimized and a better performance one is obtained by combining the Gaussian approximation algorithm and the particle swarm optimization(PSO)algorithm.Applied to the data reconciliation of continuous variables coherent states based quantum key distribution,the algorithm gets a lower SNRthreshold and improves reconciliation efficiency so that the communication distance of quantum key distribution is extended.When the SNRof quantum channel is above 4.9dB and the number of packets of continuous variables is 2×105,the simulation results of the algorithm written by C language show that the reliable data reconciliation can be realized.Meanwhile,the reconciliation efficiency can achieve 92.06%and the maximum transmission distance can be extended up to 35.5km.

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arXiv:2305.01963•Physical Review Applied•May 25, 2023•20 citations
According to the basic principle of the density evolution for the irregular low-density paritycheck(LDPC)codes,the parity check matrix His optimized and a better performance one is obtained by combining the Gaussian approximation algorithm and the particle swarm optimization(PSO)algorithm.Applied to the data reconciliation of continuous variables coherent states based quantum key distribution,the algorithm gets a lower SNRthreshold and improves reconciliation efficiency so that the communication distance of quantum key distribution is extended.When the SNRof quantum channel is above 4.9dB and the number of packets of continuous variables is 2×105,the simulation results of the algorithm written by C language show that the reliable data reconciliation can be realized.Meanwhile,the reconciliation efficiency can achieve 92.06%and the maximum transmission distance can be extended up to 35.5km.
In quantum cryptography communication,distributions of the non optimized Low Density Parity Check(LDPC) has low performance and it has low reconciliation efficiency and short transmission distance.Aiming at this problem,a quantum key distribution data coordination algorithm based on continuous variables is proposed.Take the advantage of characteristics of Extrinsic Information Transfer(EXIT) chart,from the results of Guassian approximation based on Particle Swarm Optimization(PSO),EXIT chart selects better performance distributions by comparing the threshold value and optimize LDPC code.Simulation results show that,compared with the density evolution algorithm and the Gauss approximation algorithm,the LDPC code distribution can be optimized effectively by EXIT chart.Meanwhile,when the number of packets of continuous variables is 2×105,compared with of the non optimized LDPC codes,the optimized LDPC codes can reduce the convergence Signal to Noise Ratio(SNR) and improve the reconciliation efficiency and maximum transmission distance.
Information reconciliation in the continuousvariable quantum key distribution (CVQKD) plays a vital role on affecting secret key rate as well as maximum transmission distance. It is necessary to search good error-correcting codes in order to improve the performance of reconciliation efficiency. In this work, we construct Quasi-Cyclic (QC) low-density paritycheck (LDPC) codes based on LDPC codes in the digital video broadcasting second generation terrestrial (DVB-T2) standard, and then combine these codes with information reconciliation in the CVQKD system, which can extremely ameliorate the performance of secret key rate and maximum transmission distance. The simulation results show that our proposed QC-LDPC codes can achieve higher reconciliation efficiency of 93.05% compare to DVB-T2 LDPC codes, which means our proposed QC-LDPC codes can obtain better performance of secret key rate and longer maximum transmission distance.
Abstract Quantum key distribution (QKD) is the most mature application of quantum information technology. Information reconciliation is a crucial step in QKD and significantly affects the final secret key rates shared between two legitimate parties. We analyze and compare various construction methods of low-density parity-check (LDPC) codes and design high-performance irregular LDPC codes with a block length of 10 6 . Starting from these good codes and exploiting the slice reconciliation technique based on multilevel coding and multistage decoding, we realize high-efficiency Gaussian key reconciliation with efficiency higher than 95% for signal-to-noise ratios above 1. Our demonstrated method can be readily applied in continuous variable QKD.
Information reconciliation is a significant step for a continuous-variable quantum key distribution (CV-QKD) system. We propose a reconciliation method that allows two authorized parties to extract a consistent and secure binary key in a CV-QKD protocol, which is based on Gaussian-modulated coherent states and homodyne detection. This method named spherical reconciliation is based on spherical quantization and non-binary low-density parity-check (LDPC) codes. With the suitable signal-to-noise ratio (SNR) and code rate of non-binary LDPC codes, spherical reconciliation algorithm has a high efficiency and can extend the transmission distance of CV-QKD.
An information reconciliation method for continuous-variable quantum key distribution with Gaussian modulation that is based on non-binary low-density parity-check (LDPC) codes is presented. Sets of regular and irregular LDPC codes with different code rates over the Galois fields GF(8)GF(8)GF(8), GF(16)GF(16)GF(16), GF(32)GF(32)GF(32), and GF(64)GF(64)GF(64) have been constructed. We have performed simulations to analyze the efficiency and the frame error rate using the sum-product algorithm. The proposed method achieves an efficiency between 0.940.940.94 and 0.980.980.98 if the signal-to-noise ratio is between 444 dB and 242424 dB.
Non-Gaussian modulation can improve the performance of continuous-variable quantum key distribution (CV QKD). For Gaussian-modulated coherent-state CV QKD, photon subtraction can realize non-Gaussian modulation, which can be equivalently implemented by non-Gaussian postselection. However, non-Gaussian reconciliation has not been deeply researched, which is one of the key technologies in CV QKD. In this paper, we propose a non-Gaussian reconciliation method to obtain identical keys from non-Gaussian data. Multidimensional reconciliation and multiedge-type low-density parity-check codes (MET LDPC) are used in a non-Gaussian reconciliation scheme, where the layered belief propagation decoding algorithm of MET LDPC codes is used to reduce the decoding complexity. Furthermore, we compare the error-correction performance of Gaussian data and non-Gaussian data. The results show that the error-correction performance of non-Gaussian data is better than Gaussian data, where the frame error rate can be reduced by 50 % for code rate 0.1 at SNR of 0.1554 and the average iteration number can be reduced by 25 %.