Continuous variable quantum key distribution data coordination code rate adaptive method

Abstract

The present application belongs to the field of continuous variable quantum key distribution, and particularly relates to a continuous variable quantum key distribution data coordination code rate adaptive method. The present application mainly solves the problem that the check matrix of different code rates needs to coordinate data within a certain range of signal-to-noise ratio, which leads to the fluctuation of coordination efficiency and frame error rate, thereby affecting the final key rate of the system. The present application combines RL-LDPC code and adds trusted Gaussian noise to realize adaptive data coordination with high coordination efficiency, and avoids the fluctuation of coordination efficiency and frame error rate to maximize the final key rate of the system.

Description

Technical Field

[0001] This invention belongs to the field of continuous variable quantum key distribution, and specifically relates to an adaptive method for data coordination code rate in continuous variable quantum key distribution. Background Technology

[0002] In the modern information society, information security is paramount and presents significant challenges to humanity. Quantum key distribution (QKD), based on the fundamental laws of quantum mechanics, enables two users to share a theoretically secure key. Depending on the information encoding carrier and measurement method, QKD technology is divided into discrete variable (DV) QKD and continuous variable (CV) QKD. CV-QKD uses orthogonal components of an optical field as the information carrier and can provide high key rates over metropolitan areas. Furthermore, it exhibits good compatibility with current coherent optical communication technologies and has experienced rapid development in recent years. Currently, facing the ever-growing demands of practical applications, single-rate error-correcting codes cannot achieve good coordination performance. Therefore, how to achieve highly coordinated continuous variable quantum key distribution in real-world applications has become an urgent problem to be solved.

[0003] In continuous-variable quantum key distribution (CV-QKD) systems, the performance of data coordination between the communicating parties is crucial for achieving a high key rate. One rate-adaptive method based on pruning and shortening techniques adds pruned bits (uncorrelated values ​​between Alice and Bob) and shortened bits (identical values ​​between Alice and Bob) to the original key. Simulations of the system's coordination efficiency using this method demonstrate its ability to achieve relatively stable coordination efficiency. Another rate-adaptive method based on RL-LDPC codes incorporates the error-correcting characteristics of MET-LDPC codes and the bit error rate characteristics of Raptor codes into RL-LDPC codes. Simulations of the system's coordination efficiency using this method on both CPU and GPU show that it can achieve relatively stable coordination efficiency and frame error rate under a single signal-to-noise ratio and can be applied to real-time CV-QKD systems. However, for practical real-time CV-QKD systems, the first method requires data manipulation on both Alice's and Bob's raw codes, which is overly complex and places high demands on the system's hardware implementation. The second method, which constructs RL-LDPC codes to coordinate data with raw codes within a certain range of signal-to-noise ratio variation, will inevitably lead to fluctuations in coordination efficiency and frame error rate, thus affecting the system key rate.

[0004] In view of this, the present invention provides an adaptive data coordination method for continuous variable quantum key distribution. This method combines RL-LDPC codes with the addition of trusted Gaussian noise to achieve highly efficient adaptive data coordination. In existing technologies, parity-check matrices at different code rates need to coordinate data within a certain signal-to-noise ratio range, which leads to fluctuations in coordination efficiency and frame error rate, thus affecting the final key rate of the system. The present invention effectively solves this problem and eliminates the need for cumbersome data processing at both Alice and Bob ends. By adding trusted Gaussian noise at the Bob end, the system signal-to-noise ratio is reduced to the optimal signal-to-noise ratio within the coordination range of each RL-LDPC code rate, avoiding fluctuations in coordination efficiency and frame error rate to maximize the final key rate of the system. Summary of the Invention

[0005] To address the technical problems existing in the prior art, the present invention provides a continuous variable quantum key distribution data coordination code rate adaptive method.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solution:

[0007] Step 1: Test the fluctuation range of the signal-to-noise ratio of the continuous variable quantum key distribution system, and construct the RL-LDPC code with the corresponding code rate based on the fluctuation range;

[0008] Step 2: Estimate the current signal-to-noise ratio by estimating the parameters in the continuous variable quantum key distribution system, and select an RL-LDPC code with an appropriate code rate;

[0009] Step 3: Bob calculates the variance V that needs to be added with random, reliable Gaussian noise. n And generate random, reliable Gaussian noise with corresponding variance, and add it to the raw code data;

[0010] Step 4: Bob encodes the data and sends the edge information and checksum to Alice.

[0011] Step 5: Alice receives the edge information and checksum, selects the RL-LDPC code with the corresponding code rate based on their length, and performs decoding and error correction.

[0012] Step 1 specifically includes:

[0013] Step 1.1: Test the fluctuation range of the signal-to-noise ratio (SNR) of the continuous-variable quantum key distribution system to obtain the maximum SNR. max and minimum signal-to-noise ratio (SNR) min The signal-to-noise ratio (SNR) condition for system operation must be met. min < <SNR<<SNR max ;

[0014] Step 1.2: Based on the signal-to-noise ratio fluctuation range obtained from the test, and by selecting the coordinated signal-to-noise ratio interval for each different code rate RL-LDPC code, construct the corresponding RL-LDPC code parity check matrix;

[0015] Step 1.3: Use the signal-to-noise ratio (SNR) at which the maximum key rate can be obtained for each RL-LDPC code as the initial SNR for the coordinated SNR range of that RL-LDPC code.

[0016] Furthermore, the RL-LDPC code parity-check matrix for the corresponding code rate is constructed by cutting and expanding, as shown in the following formula:

[0017]

[0018]

[0019] Where R represents the bitrate to be adjusted, n represents the number of variable nodes, m represents the number of check nodes, and c and d represent the number of nodes to be cut and expanded, respectively.

[0020] Step 3 specifically includes:

[0021] Step 3.1: Bob's end uses the initial signal-to-noise ratio of the selected RL-LDPC code, the relevant parameters of the current continuous variable quantum key distribution system obtained from parameter estimation, and the modulation variance V at Alice's end. A The variance V of the random, reliable Gaussian noise to be added is obtained. n The formula is as follows:

[0022]

[0023] Where T represents quantum channel transmittance, η represents detection efficiency, ε represents excess noise, and V el SNR represents electronic noise;

[0024] The Bob end can also calculate the variance V of the random reliable Gaussian noise to be added based on the initial signal-to-noise ratio of the selected RL-LDPC code, the correlation between the data from Alice and Bob ends, and the variance of the probe data from Bob end. n The formula is as follows:

[0025]

[0026] Among them, V B ρ represents the variance of the probe data at Bob's end, and ρ represents the correlation between the data at Alice's end and Bob's end.

[0027] Step 3.2: Bob selects to generate random, reliable Gaussian noise data with the corresponding variance, and the data length is the same as the raw code data length;

[0028] Step 3.3: Bob adds the generated random, reliable Gaussian noise data to the initial raw code data as multidimensional coordinated coding data.

[0029] Step 4 specifically includes:

[0030] Step 4.1: Bob performs multidimensional coordinated coding on the multidimensional coordinated coding data after adding random trusted Gaussian noise, generating side information and checksums;

[0031] Step 4.2: Send the generated edge information and checksum to the Alice terminal via the classic channel.

[0032] Step 5 specifically includes:

[0033] Step 5.1: Alice receives the edge information and the length of the checksum, and selects an RL-LDPC code that matches Bob's length.

[0034] Step 5.2: Alice uses the selected RL-LDPC code for decoding and error correction.

[0035] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0036] The quantum channel in a QKD system is a time-varying channel, and its channel characteristics can change due to variations in the surrounding environment and equipment imperfections, leading to fluctuations in the system's signal-to-noise ratio (SNR). Since the number of parity-check matrices constructed for different code rates is finite, existing technologies require coordinating data within a certain SNR range for these matrices. This inevitably leads to fluctuations in coordination efficiency and frame error rate, thus affecting the final key rate. This invention effectively solves this problem without requiring cumbersome data processing at both Alice and Bob ends. By adding trusted Gaussian noise at the Bob end, the system SNR is reduced to the optimal SNR within the coordination range for each RL-LDPC code rate, avoiding fluctuations in coordination efficiency and frame error rate to maximize the final key rate. Attached Figure Description

[0037] Figure 1 This is a flowchart of the method used in this invention. Detailed Implementation

[0038] To facilitate understanding of the present invention, a more comprehensive description will be given below. However, the present invention can be implemented in many different forms and is not limited to the embodiments described herein. Rather, these embodiments are provided to provide a thorough and complete understanding of the disclosure of the present invention.

[0039] Example 1

[0040] A continuous-variable quantum key distribution data coordination rate adaptive method, such as Figure 1 As shown, it includes the following steps:

[0041] Step 1: Test the fluctuation range of the signal-to-noise ratio of the continuous variable quantum key distribution system, and construct the RL-LDPC code with the corresponding code rate based on the fluctuation range;

[0042] Step 1.1: Test the fluctuation range of the signal-to-noise ratio (SNR) of the continuous-variable quantum key distribution system to obtain the maximum SNR. max and minimum signal-to-noise ratio (SNR) min The signal-to-noise ratio (SNR) condition for system operation must be met. min < <SNR<<SNR max ;

[0043] Step 1.2: Based on the signal-to-noise ratio fluctuation range obtained from the test, and selecting the signal-to-noise ratio coordination interval for each different code rate RL-LDPC code, construct the corresponding RL-LDPC code parity-check matrix; construct the corresponding RL-LDPC code parity-check matrix by cutting and expanding, as shown in the following formula:

[0044]

[0045]

[0046] Where R represents the bitrate to be adjusted, n represents the number of variable nodes, m represents the number of check nodes, and c and d represent the number of nodes to be cut and expanded, respectively.

[0047] Step 1.3: Use the signal-to-noise ratio (SNR) at which the maximum key rate can be obtained for each RL-LDPC code as the initial SNR for the coordinated SNR range of that RL-LDPC code.

[0048] Step 2: Estimate the current signal-to-noise ratio by estimating the parameters in the continuous variable quantum key distribution system, and select an RL-LDPC code with an appropriate code rate;

[0049] Step 3: Bob calculates the variance V that needs to be added with random, reliable Gaussian noise. n And generate random, reliable Gaussian noise with corresponding variance, and add it to the raw code data;

[0050] Step 3.1: Bob's end uses the initial signal-to-noise ratio of the selected RL-LDPC code, the relevant parameters of the current continuous variable quantum key distribution system obtained from parameter estimation, and the modulation variance V at Alice's end. A The variance V of the random, reliable Gaussian noise to be added is obtained. n The formula is as follows:

[0051]

[0052] Where T represents quantum channel transmittance, η represents detection efficiency, ε represents excess noise, and V el SNR represents electronic noise;

[0053] The Bob end can also calculate the variance V of the random reliable Gaussian noise to be added based on the initial signal-to-noise ratio of the selected RL-LDPC code, the correlation between the data from Alice and Bob ends, and the variance of the probe data from Bob end. n The formula is as follows:

[0054]

[0055] Among them, V B ρ represents the variance of the probe data at Bob's end, and ρ represents the correlation between the data at Alice's end and Bob's end.

[0056] Step 3.2: Bob selects to generate random, reliable Gaussian noise data with the corresponding variance, and the data length is the same as the raw code data length;

[0057] Step 3.3: Bob adds the generated random, reliable Gaussian noise data to the initial raw code data as multidimensional coordinated coding data.

[0058] Step 4: Bob encodes the data and sends the edge information and checksum to Alice.

[0059] Step 4.1: Bob performs multidimensional coordinated coding on the multidimensional coordinated coding data after adding random trusted Gaussian noise, generating side information and checksums;

[0060] Step 4.2: Send the generated edge information and checksum to the Alice terminal via the classic channel.

[0061] Step 5: Alice receives the edge information and checksum, selects the RL-LDPC code with the corresponding code rate based on their length, and performs decoding and error correction.

[0062] Step 5.1: Alice receives the edge information and the length of the checksum, and selects an RL-LDPC code that matches Bob's length.

[0063] Step 5.2: Alice uses the selected RL-LDPC code for decoding and error correction.

[0064] Simulation results show that, within the ideal signal-to-noise ratio of 0.16 and a fluctuation range of 15%, this method can maintain a high coordination efficiency of over 94.4% and a low frame error rate.

[0065] The above embodiments illustrate how to utilize RL-LDPC codes combined with added trusted Gaussian noise in a continuous-variable quantum key distribution system for adaptive code rate data coordination. This solves the problem of the security key rate being affected by system signal-to-noise ratio fluctuations. The adaptive code rate method for continuous-variable quantum key distribution data coordination proposed in this invention can stabilize coordination efficiency and frame error rate, improve the system key rate, and can be applied to real-time CV-QKD systems in practical application scenarios.

Claims

1. A continuous-variable quantum key distribution data coordination rate adaptive method, characterized in that, Includes the following steps: Step 1: Test the fluctuation range of the signal-to-noise ratio of the continuous variable quantum key distribution system, and construct the RL-LDPC code with the corresponding code rate based on the fluctuation range; Step 2: Estimate the current signal-to-noise ratio by estimating the parameters in the continuous variable quantum key distribution system, and select an RL-LDPC code with an appropriate code rate; Step 3: Bob calculates the variance that needs to be added with random, reliable Gaussian noise. And generate random, reliable Gaussian noise with corresponding variance, and add it to the raw code data; Step 4: Bob encodes the data and sends the edge information and checksum to Alice. Step 5: Alice receives the edge information and checksum, selects the RL-LDPC code with the corresponding code rate based on their length, and performs decoding and error correction. The variance The calculation formula is as follows (3) or (4): （3） in, Modulation variance for the Alice end, Indicates quantum channel transmittance, Indicates detection efficiency, Indicates excessive noise, Indicates electronic noise, Indicates the signal-to-noise ratio; （4） in, The variance of the probe data at the Bob end. The correlation between the data on Alice's end and Bob's end.

2. The continuous-variable quantum key distribution data coordination code rate adaptive method according to claim 1, characterized in that, Step 1 specifically includes: Step 1.1: Test the fluctuation range of the signal-to-noise ratio (SNR) of the continuous-variable quantum key distribution system to obtain the maximum SNR. and minimum signal-to-noise ratio The signal-to-noise ratio condition for system operation is met, i.e. ; Step 1.2: Based on the signal-to-noise ratio fluctuation range obtained from the test, and by selecting the coordinated signal-to-noise ratio interval for each different code rate RL-LDPC code, construct the corresponding RL-LDPC code parity check matrix; Step 1.3: Use the signal-to-noise ratio (SNR) at which the maximum key rate can be obtained for each RL-LDPC code as the initial SNR for the coordinated SNR range of that RL-LDPC code.

3. The continuous variable quantum key distribution data coordination code rate adaptive method according to claim 2, characterized in that, The RL-LDPC code parity check matrix for the corresponding code rate is constructed by cutting and expanding, as shown in the following formula: （1） （2） in, This indicates the bitrate you want to adjust. Indicates the number of variable nodes. Indicates the number of verification nodes. and These represent the number of nodes that need to be cut and expanded, respectively.

4. The continuous variable quantum key distribution data coordination code rate adaptive method according to claim 2, characterized in that, Step 3 specifically includes: Step 3.1: Bob's end uses the initial signal-to-noise ratio of the selected RL-LDPC code, the relevant parameters of the current continuous variable quantum key distribution system obtained from parameter estimation, and the modulation variance at Alice's end. The variance of the random, reliable Gaussian noise to be added is obtained. ; Step 3.2: Bob selects to generate random, reliable Gaussian noise data with the corresponding variance, and the data length is the same as the raw code data length; Step 3.3: Bob adds the generated random, reliable Gaussian noise data to the initial raw code data as multidimensional coordinated coding data.

5. The continuous variable quantum key distribution data coordination code rate adaptive method according to claim 2, characterized in that, Step 3 specifically includes: Step 3.1: Based on the initial signal-to-noise ratio of the selected RL-LDPC code, the correlation between the data from Alice and Bob's ends, and the variance of the probe data from Bob's end, Bob's end jointly calculates the variance of the random reliable Gaussian noise to be added. ; Step 3.2: Bob selects to generate random, reliable Gaussian noise data with the corresponding variance, and the data length is the same as the raw code data length; Step 3.3: Bob adds the generated random, reliable Gaussian noise data to the initial raw code data as multidimensional coordinated coding data.

6. The continuous variable quantum key distribution data coordination code rate adaptive method according to claim 4, characterized in that, Step 4 specifically includes: Step 4.1: Bob performs multidimensional coordinated coding on the multidimensional coordinated coding data after adding random trusted Gaussian noise, generating side information and checksums; Step 4.2: Send the generated edge information and checksum to the Alice terminal via the classic channel.

7. The continuous-variable quantum key distribution data coordination code rate adaptive method according to claim 6, characterized in that, Step 5 specifically includes: Step 5.1: Alice receives the edge information and the length of the checksum, and selects an RL-LDPC code that matches Bob's length. Step 5.2: Alice uses the selected RL-LDPC code for decoding and error correction.

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