Continuous variable quantum key distribution negotiation method and system based on S-ET

Abstract

The present invention provides a continuous variable quantum key distribution negotiation method and system based on S-ET, including: Alice generates a random sequence R based on a quantum random number generator. k and the LDPC code check matrix to calculate the side information Syndrome sequence S, and send it to Bob through the classic public channel; Alice sends R k After LDPC code encoding and spherical mapping, the mapping function M is calculated on the normalized Gaussian sequence y and sent to Bob through the classical public channel; Bob maps the normalized Gaussian sequence x through the mapping function to obtain v n ; Bob will v n , LDPC code check matrix, maximum number of iterations, and S are sent to the decoder input; the decoder calculates the synthesized sequence S at each decoding iteration. de ET operation is performed by checking consistency with S. The present invention can determine whether the current decoding can continue to correct errors and perform ET operation to abandon the current frame, thereby improving the system decoding speed, negotiation system efficiency and final key rate.

Description

Technical Field

[0001] The present invention relates to the field of quantum communication technology, and in particular to a continuous variable quantum key distribution (CVQKD) negotiation method based on early termination of decoding (ET) (S-ET) based on side information Syndrome consistency in information negotiation, and in particular to a continuous variable quantum key distribution negotiation method and system based on S-ET. Background Art

[0002] Quantum key distribution (QKD) technology as a whole is divided into two categories: discrete variable quantum key distribution (DVQKD) and continuous variable quantum key distribution (CVQKD). Compared with discrete variable quantum key distribution technology, continuous variable quantum key distribution technology has higher communication rate and efficiency. Therefore, it has attracted many research institutions in the world to conduct in-depth research on its theory and application technology. At the same time, it is also because of this that continuous variable quantum secure communication technology has become an important branch of the entire secure communication technology.

[0003] CVQKD technology can ensure unconditional and secure key distribution based on the basic physics theory of quantum. This advantage is extremely consistent with the requirements of one-time pad technology. Therefore, we can combine one-time pad technology with CVQKD technology to fight against the extremely strong computing power of quantum computers. CVQKD technology is divided into two parts, one is the quantum communication part of the physical layer, and the other is its post-processing part. Due to the existence of eavesdropper Eve in actual communication, the keys obtained by the communicating parties may be asymmetric, so it is necessary to rely on post-processing technology to process the original key so that it is consistent and secure between the communicating parties.

[0004] Since the deployment of the CVQKD system may be greatly affected by the environment, resulting in a very low signal-to-noise ratio in the current environment, we often need to configure LDPC codes with longer code lengths for use in post-processing information negotiations, or increase the maximum number of decoding iterations in the negotiation. However, these operations will increase the complexity of encoding and decoding, reduce the efficiency of the information negotiation system and the key generation rate. And as quantum communication technology at the physical layer becomes more mature, the processing speed of the physical link part has increased significantly. Therefore, the speed of post-processing is seriously out of sync with the speed of quantum communication, which will restrict the overall process of the CVQKD system.

[0005] The invention patent with publication number CN106788706B discloses a continuous variable quantum key distribution method that can resist actual attacks, including: step A: continuous variable quantum information transmission; step B: data post-processing step including pre-processing operation, which means that Bob obtains the original key based on peak-to-valley value search and Gaussian post-selection, and obtains accurate parameter evaluation in combination with real-time monitored local oscillator intensity evaluation, and finally performs data post-processing to obtain the final key. Summary of the invention

[0006] In view of the defects in the prior art, the present invention provides a continuous variable quantum key distribution negotiation method and system based on S-ET.

[0007] According to a continuous variable quantum key distribution negotiation method and system based on S-ET provided by the present invention, the scheme is as follows:

[0008] In a first aspect, a continuous variable quantum key distribution negotiation method based on S-ET is provided, the method comprising:

[0009] Step S1: In the CVQKD information negotiation, Alice transmits the Gaussian sequence X to Bob through the quantum channel to obtain the Gaussian sequence Y, where Y = X + Z, and Z is the quantum channel noise;

[0010] Step S2: Alice and Bob divide their respective Gaussian sequences into several groups, each of which contains n elements, where n is the dimension of multi-dimensional information negotiation; then Alice and Bob normalize their own Gaussian sequences to obtain x and y respectively;

[0011] Step S3: The quantum random number generator generates a random binary sequence R k , this sequence is encoded by LDPC code to get e n Then convert it into a binary spherical sequence u n ;

[0012] Through y and the spherical sequence u n , Bob calculates the mapping function M(y,u n ), at the same time, Bob is connected to n The LDPC code check matrix H is used to calculate the Syndrome to obtain the sequence S, and the mapping function and the sequence S are sent to Alice through the classical public channel;

[0013] Step S4: After receiving the mapping function, Alice maps her Gaussian sequence x into v n , input it and the parameters including the check matrix H, the maximum number of iterations and the sequence S into the decoder for decoding;

[0014] Step S5: Decoding is terminated when the decoder meets the S-ET criterion; or the S calculated in each decoding iteration is de Decoding is terminated when it is equal to sequence S; or decoding is terminated when the number of decoding iterations reaches the set maximum number of iterations;

[0015] Step S6: The decoder outputs the processed sequence If the decoding is successful, Then Alice and Bob share a set of symmetric keys; otherwise, the decoding fails and the above steps are repeated.

[0016] Preferably, the specific calculation formulas for x and y in step S2 are:

[0017] x=X / ‖X‖

[0018] y=Y / ‖Y‖

[0019] in, ‖.‖ represents the norm; <,> represents the inner product.

[0020] Preferably, step S3 comprises: To perform binary spherical conversion; by S = H × e n Get the Syndrome sequence.

[0021] Preferably, the step S5 includes: the decoding system first performs S-ET judgment, and then judges S de Is it equal to the sequence S, or whether the maximum number of iterations set is reached.

[0022] Preferably, the step S5 specifically includes:

[0023] Step S5.1: Initialize parameters, set parameter values ​​λ and P, and reset the counter;

[0024] Step S5.2: After the i-th decoding iteration, calculate S de (i) Perform an XOR operation with the received sequence S and find the sum of the different numbers S xor (i);

[0025] Step S5.3: Calculate S after the i-th decoding iteration xor Mean(i>1): If |E[S xor (i)]-E[S xor (i-1)]|<λE[S xor (i-1)], the counter is incremented by one, otherwise the counter is reset;

[0026] Step S5.4: If the counter reaches P, the decoding is terminated.

[0027] In a second aspect, a continuous variable quantum key distribution negotiation system based on S-ET is provided, the system comprising:

[0028] Module M1: In CVQKD information negotiation, Alice transmits Gaussian sequence X to Bob through the quantum channel to obtain Gaussian sequence Y, where Y = X + Z, and Z is the quantum channel noise;

[0029] Module M2: Alice and Bob divide their respective Gaussian sequences into several groups, each of which contains n elements, where n is the dimension of multi-dimensional information negotiation; then Alice and Bob normalize their own Gaussian sequences to obtain x and y respectively;

[0030] Module M3: Quantum random number generator generates a random binary sequence R k , this sequence is encoded by LDPC code to get e n Then convert it into a binary spherical sequence u n ;

[0031] Through y and the spherical sequence u n , Bob calculates the mapping function M(y,u n ), at the same time, Bob is connected to n The LDPC code check matrix H is used to calculate the Syndrome to obtain the sequence S, and the mapping function and the sequence S are sent to Alice through the classical public channel;

[0032] Module M4: Alice receives the mapping function and maps its Gaussian sequence x into v n , input it and the parameters including the check matrix H, the maximum number of iterations and the sequence S into the decoder for decoding;

[0033] Module M5: Decoding is terminated when the decoder meets the S-ET judgment criteria; or when the S calculated in each decoding iteration is de Decoding is terminated when it is equal to sequence S; or decoding is terminated when the number of decoding iterations reaches the set maximum number of iterations;

[0034] Module M6: Decoder output terminal outputs the processed sequence If the decoding is successful, Then Alice and Bob share a set of symmetric keys; otherwise, the decoding fails and the above modules are repeated.

[0035] Preferably, the specific calculation formulas for x and y in the module M2 are:

[0036] x=X / ‖X‖

[0037] y=Y / ‖Y‖

[0038] in, ‖.‖ represents the norm; <,> represents the inner product.

[0039] Preferably, the module M3 comprises: To perform binary spherical conversion; by S = H × e n Get the Syndrome sequence.

[0040] Preferably, the module M5 includes: the decoding system first performs S-ET judgment, and then judges S de Is it equal to the sequence S, or whether the maximum number of iterations set is reached.

[0041] Preferably, the module M5 specifically includes:

[0042] Step S5.1: Initialize parameters, set parameter values ​​λ and P, and reset the counter;

[0043] Step S5.2: After the i-th decoding iteration, calculate S de (i) Perform an XOR operation with the received sequence S and find the sum of the different numbers S xor (i);

[0044] Step S5.3: Calculate S after the i-th decoding iteration xor Mean(i>1): If |E[S xor (i)]-e[S xor (i-1)]|<λE[S xor (i-1)], the counter is incremented by one, otherwise the counter is reset;

[0045] Step S5.4: If the counter reaches P, the decoding is terminated.

[0046] Compared with the prior art, the present invention has the following beneficial effects:

[0047] 1. According to the relationship between the Syndrome change model and the decoding effect, the present invention terminates the information negotiation in the CVQKD post-processing in advance to obtain the post-processing key, which greatly reduces the running time of the traditional decoding system, shortens the physical link and the post-processing time gap, and improves the negotiation system efficiency and the final key rate;

[0048] 2. The present invention utilizes the saved time to conduct multiple information negotiations, thereby increasing the amount of mutual information between the communicating parties and further improving the final key rate in the CVQKD system. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Other features, objects and advantages of the present invention will become more apparent from the detailed description of non-limiting embodiments made with reference to the following drawings:

[0050] Figure 1 Schematic diagram of quantum channel transmission between Alice and Bob in the present invention;

[0051] Figure 2 It is a logic diagram of the steps of the continuous variable quantum key distribution negotiation method of S-ET of the present invention;

[0052] Figure 3 It is a trend diagram of the side information Syndrome change of the continuous variable quantum key distribution negotiation method of S-ET of the present invention;

[0053] Figure 4 It is a β&FER comparison diagram of the traditional decoding system of the S-ET continuous variable quantum key distribution negotiation method of the present invention and the S-ET method under various parameters;

[0054] Figure 5 It is a β&time comparison diagram of the traditional decoding system of the S-ET continuous variable quantum key distribution negotiation method of the present invention and the S-ET method under various parameters;

[0055] Figure 6 This is a comparison chart of the distance & final secret key rate of the traditional decoding system of the S-ET continuous variable quantum key distribution negotiation method of the present invention and the S-ET method under specific parameters. DETAILED DESCRIPTION

[0056] The present invention is described in detail below in conjunction with specific embodiments. The following embodiments will help those skilled in the art to further understand the present invention, but are not intended to limit the present invention in any form. It should be noted that, for those of ordinary skill in the art, several changes and improvements can also be made without departing from the concept of the present invention. These all belong to the protection scope of the present invention.

[0057] The embodiment of the present invention provides a continuous variable quantum key distribution negotiation method based on S-ET, referring to Figure 1 and Figure 2 As shown, the method includes:

[0058] Step S1: In CVQKD information negotiation, Alice transmits the Gaussian sequence X to Bob through the quantum channel to obtain the Gaussian sequence Y, where Y=X+Z, and Z is the quantum channel noise.

[0059] Step S2: Alice and Bob divide their respective Gaussian sequences into several groups, each group contains n elements, where n is the dimension of multi-dimensional information negotiation; then Alice and Bob normalize their own Gaussian sequences to obtain x and y respectively.

[0060] The specific calculation formulas of x and y in step S2 are:

[0061] x=X / ‖X‖

[0062] y=Y / ‖Y‖

[0063] in, ‖.‖ represents the norm; <,> represents the inner product.

[0064] Step S3: The quantum random number generator generates a random binary sequence R k , this sequence is encoded by LDPC code to get e n Then convert it into a binary spherical sequence u n .

[0065] Through y and the spherical sequence u n , Bob calculates the mapping function M(y,u n ), at the same time, Bob is connected to n And the LDPC code check matrix H is used to calculate Syndrome to obtain the sequence S, and the mapping function and sequence S are sent to Alice through the classical public channel.

[0066] In step S3, specifically, by To perform binary spherical conversion; by S = H × e n Get the Syndrome sequence.

[0067] Step S4: After receiving the mapping function, Alice maps her Gaussian sequence x into v n , and input it into the decoder with parameters such as the check matrix H, the maximum number of iterations, and the sequence S for decoding.

[0068] Step S5: Decoding is terminated when the decoder meets the S-ET criterion; or the S calculated in each decoding iteration is de The decoding is terminated when it is equal to the sequence S; or the decoding iteration number reaches the set maximum number of iterations.

[0069] In this step, the decoding system first performs S-ET judgment, and then judges S de Is it equal to the sequence S, or whether the maximum number of iterations set is reached.

[0070] Step S5 specifically includes:

[0071] Step S5.1: Initialize parameters, set parameter values ​​λ and P, and reset the counter;

[0072] Step S5.2: After the i-th decoding iteration, calculate S de (i) Perform an XOR operation with the received sequence S and find the sum of the different numbers S xor (i);

[0073] Step S5.3: Calculate S after the i-th decoding iteration xor Mean(i>1): If |E[S xor (i)]-e[S xor (i-1)]|<λE[S xor (i-1)], the counter is incremented by one, otherwise the counter is reset;

[0074] Step S5.4: If the counter reaches P, the decoding is terminated.

[0075] Step S6: The decoder outputs the processed sequence If the decoding is successful, Then Alice and Bob share a set of symmetric keys; otherwise, the decoding fails and the above steps are repeated.

[0076] Next, the present invention will be described in more detail.

[0077] Due to the existence of the eavesdropper Eve and the influence of various harsh environments, the CVQKD system includes not only the quantum communication part of the physical layer, but also the post-processing part for obtaining the symmetric key. The performance of the negotiation part in the post-processing not only affects the key generation rate of the CVQKD system, but also affects the maximum transmission distance of the system. The negotiation part is divided into forward negotiation and reverse negotiation. This embodiment adopts reverse negotiation with a longer transmission distance and multilateral LDPC codes with extremely wide application scenarios.

[0078] Alice sends the Gaussian sequence to Bob through the quantum channel, and both parties normalize their own sequences to obtain x and y. The quantum random number generator on Bob's end generates a random sequence R k , this sequence is encoded by a multilateral LDPC code to obtain the sequence e n , then calculate the side information Syndrome to get the sequence S = H × e n And the spherical mapping of the encoded sequence is used to calculate the mapping function M(y,u n ), whose characteristic is that M(y,u n )×y=u n .

[0079] Bob sends the calculated mapping function and side information Syndrome to Alice through the classic public channel. Alice maps x to get v n =M(y,u n )×x, and sends it to the decoder input end along with S, the multilateral LDPC code check matrix H, the set maximum number of iterations 300 and other parameters.

[0080] When the decoder performs iterative operations, we can obtain the current calculated S de The correlation and change trend between S and Figure 3 As shown, S de As the number of iterations increases, it will tend to be consistent with S, that is, as the number of iterations increases, S de The sum of different numbers of S will converge, and the S-ET judgment standard can be used to judge the current S de Whether the sum of different numbers from S converges.

[0081] Set the initialization parameters λ, P in advance and reset the counter. After the i-th decoding iteration, calculate S de (i) Perform an XOR operation with the received S and calculate the sum of their different numbers S xor (i). Calculate S after the i-th decoding iteration xor Mean (300≥i>1): If |E[S xor (i)]-E[S xor (i-1)]|<λE[S xor (i-1)], the counter is incremented, otherwise the counter is reset. If the counter reaches P, the decoding is terminated. If the decoding system does not terminate the decoding in the S-ET judgment module, it continues to iterate until the maximum number of iterations set or S de =S, the decoding is terminated.

[0082] Reference Figure 4 and Figure 5 As shown in the figure, the β&FER and β&time comparison diagrams of the traditional decoding system and the S-ET method under various parameters are shown. The S-ET algorithm increases the FER by a small amount in exchange for a large reduction in decoding time, which improves the system efficiency compared with the traditional decoding system. From the simulation results, it can be concluded that the smaller the parameter λ is and the larger the P is, the more rigorous the S-ET method will judge the degree of convergence, and the S-ET method will lose less FER compared with the traditional decoding system, but the time saved will also be less; on the contrary, the larger the parameter λ is and the smaller the P is, the looser the S-ET method will judge the degree of convergence, and the S-ET method will lose more FER compared with the traditional decoding system, but the time saved will also be more.

[0083] Refer to Table 1 below, which shows the performance comparison between the S-ET method with λ=0.006 and P=2 and the traditional method under several SNR conditions. From the simulation results, we can clearly see that under low SNR, the S-ET method can greatly reduce the average number of iterations, reduce decoding time, and improve system efficiency. When the SNR is lower and the FER is higher, the average number of S-ET iterations is lower. This is because at lower SNR, S de The faster the sum of different numbers of S converges, the faster the decoding is terminated. At high SNR, the S calculated by the decoding system is de It will quickly become equal to the received S, so the reliance on S-ET is not as high as in the case of low SNR. However, since high negotiation efficiency will lead to higher key rates and longer transmission distances, and from the formula β=R / C and C=0.5log2(1+SNR), we can know that under a given bit rate, the lower the SNR, the smaller the channel capacity, and further obtain a greater negotiation efficiency β. Therefore, S-ET is very useful in improving decoding speed at low SNR.

[0084] Table 1

[0085]

[0086] Reference Figure 6 As shown in the figure, the distance & final key rate comparison diagram of the traditional negotiation and S-ET negotiation method under the same parameter conditions. From the simulation results, it can be seen that the S-ET negotiation method has a higher final key rate under a given transmission distance. According to the final key formula K fianl =(1-FER)(βI AB -X BE ), S-ET greatly improves the decoding speed and the efficiency of the negotiation system at the cost of slightly increasing FER, allowing the post-processing part to perform multiple negotiations and increasing the mutual information between the two parties. Overall, the final key rate obtained by the CVQKD system is improved.

[0087] The embodiment of the present invention provides a continuous variable quantum key distribution negotiation method and system based on S-ET. The method for quickly generating post-processing keys based on the Syndrome change model adds an S-ET judgment step to the traditional decoding system. Bob sends the side information Syndrome to Alice through the classical public channel to assist the decoder in decoding. After each decoding iteration of the decoder, the calculated Syndrome will also change accordingly. According to its change model, we can know the effect or status of the current decoding. When the decoding system in the negotiation iterates to a certain number of times, we can determine whether the current decoding can continue to correct the original key and perform the ET operation. When the decoding system passes the S-ET judgment, there is no need to continue the decoding iteration to abandon the current frame. Compared with the traditional decoding system, the overall efficiency of the decoding system is improved, and the efficiency of the negotiation system and the key generation rate are further improved.

[0088] Those skilled in the art know that, in addition to realizing the system and its various devices, modules, and units provided by the present invention in a purely computer-readable program code, it is entirely possible to realize the same functions in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers by logically programming the method steps. Therefore, the system and its various devices, modules, and units provided by the present invention can be considered as a hardware component, and the devices, modules, and units included therein for realizing various functions can also be regarded as structures within the hardware component; the devices, modules, and units for realizing various functions can also be regarded as both software modules for realizing the method and structures within the hardware component.

[0089] The above describes the specific embodiments of the present invention. It should be understood that the present invention is not limited to multilateral LDPC codes, but is also applicable to post-processing systems that apply other error correction codes. Those skilled in the art may make various changes or modifications within the scope of the claims, which do not affect the essence of the present invention. In the absence of conflict, the embodiments of the present application and the features in the embodiments may be combined with each other at will.

Claims

1. A continuous variable quantum key distribution negotiation method based on S-ET, characterized in that: include: Step S1: In the CVQKD information negotiation, Alice transmits the Gaussian sequence X to Bob through the quantum channel to obtain the Gaussian sequence Y, where Y = X + Z, and Z is the quantum channel noise; Step S2: Alice and Bob divide their respective Gaussian sequences into several groups, each of which contains n elements, where n is the dimension of multi-dimensional information negotiation; then Alice and Bob normalize their own Gaussian sequences to obtain x and y respectively; Step S3: The quantum random number generator generates a random binary sequence R k , this sequence is encoded by LDPC code to get e n Then convert it into a binary spherical sequence u n ; Through y and the spherical sequence u n , Bob calculates the mapping function M(y,u n ), at the same time, Bob is connected to n and the LDPC code check matrix H to calculate the Syndrome sequence S, and send the mapping function and sequence S to Alice through the classical public channel; Step S4: After receiving the mapping function, Alice maps her Gaussian sequence x into v n , input it and the parameters including the check matrix H, the maximum number of iterations and the sequence S into the decoder for decoding; Step S5: Decoding is terminated when the decoder meets the S-ET criterion; or when the S calculated in each decoding iteration is de When it is equal to sequence S, the decoding is terminated; Or the decoding is terminated when the number of decoding iterations reaches the set maximum number of iterations; Step S6: The decoder outputs the processed sequence If the decoding is successful, Then Alice and Bob share a set of symmetric keys; otherwise, the decoding fails and the above steps are repeated.

2. The continuous variable quantum key distribution negotiation method based on S-ET according to claim 1, characterized in that: The specific calculation formulas for x and y in step S2 are: x=X / ‖X‖ y=Y / ‖Y‖ in, ‖.‖ represents the norm; <,> represents the inner product.

3. The continuous variable quantum key distribution negotiation method based on S-ET according to claim 1, characterized in that: The step S3 comprises: To perform binary spherical transformation; Syndrome sequence S = H × e n .

4. The continuous variable quantum key distribution negotiation method based on S-ET according to claim 1, characterized in that: The step S5 includes: the decoding system first performs S-ET judgment, and then judges S de Is it equal to the sequence S, or whether the maximum number of iterations set is reached.

5. The continuous variable quantum key distribution negotiation method based on S-ET according to claim 1, characterized in that: The step S5 specifically includes: Step S5.1: Initialize parameters, set parameter values ​​λ and P, and reset the counter; Step S5.2: After the i-th decoding iteration, calculate S de (i) Perform an XOR operation with the received sequence S and find the sum of the different numbers S xor (i); Step S5.3: Calculate S after the i-th decoding iteration xor Mean(i>1): If |E[S xor (i)]-E[S xor (i-1)]|<λE[D xor (i-1)], the counter is incremented, otherwise the counter is reset; Step S5.4: If the counter reaches P, the decoding is terminated.

6. A continuous variable quantum key distribution negotiation system based on S-ET, characterized in that: include: Module M1: In CVQKD information negotiation, Alice transmits Gaussian sequence X to Bob through the quantum channel to obtain Gaussian sequence Y, where Y = X + Z, and Z is the quantum channel noise; Module M2: Alice and Bob divide their respective Gaussian sequences into several groups, each of which contains n elements, where n is the dimension of multi-dimensional information negotiation; then Alice and Bob normalize their own Gaussian sequences to obtain x and y respectively; Module M3: Quantum random number generator generates a random binary sequence R k , this sequence is encoded by LDPC code to get e n Then convert it into a binary spherical sequence u n ; Through y and the spherical sequence u n , Bob calculates the mapping function M(y,u n ), at the same time, Bob is connected to n and the LDPC code check matrix H to calculate the Syndrome sequence S, and send the mapping function and sequence S to Alice through the classical public channel; Module M4: Alice receives the mapping function and maps its Gaussian sequence x into v n , input it and the parameters including the check matrix H, the maximum number of iterations and the sequence S into the decoder for decoding; Module M5: Decoding is terminated when the decoder meets the S-ET judgment criteria; or when the S calculated in each decoding iteration is de When it is equal to sequence S, the decoding is terminated; Or the decoding is terminated when the number of decoding iterations reaches the set maximum number of iterations; Module M6: Decoder output terminal outputs the processed sequence If the decoding is successful, Then Alice and Bob share a set of symmetric keys; otherwise, the decoding fails and the above modules are repeated.

7. The S-ET-based continuous variable quantum key distribution negotiation system according to claim 6, characterized in that: The specific calculation formulas for x and y in the module M2 are: x=X / ‖X‖ y=Y / ‖Y‖ in, ‖.‖ represents the norm; <,> represents the inner product.

8. The S-ET-based continuous variable quantum key distribution negotiation system according to claim 6, characterized in that: The module M3 includes: To perform binary spherical transformation; Syndrome sequence S = H × e n .

9. The S-ET-based continuous variable quantum key distribution negotiation system according to claim 6, characterized in that: The module M5 includes: the decoding system first performs S-ET judgment, and then judges S de Is it equal to the sequence S, or whether the maximum number of iterations set is reached.

10. The S-ET-based continuous variable quantum key distribution negotiation system according to claim 6, characterized in that: The module M5 specifically includes: Step S5.1: Initialize parameters, set parameter values ​​λ and P, and reset the counter; Step S5.2: After the i-th decoding iteration, calculate S de (i) Perform an XOR operation with the received sequence S and find the sum of the different numbers S xor (i); Step S5.3: Calculate S after the i-th decoding iteration xor Mean(i>1): If |E[S xor (i)]-E[S xor (i-1)]|<λE[S xor (i-1)], the counter is incremented, otherwise the counter is reset; Step S5.4: If the counter reaches P, the decoding is terminated.

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