CN111786681A - Cascade decoding method suitable for data post-processing of CV-QKD system - Google Patents
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Abstract
The invention relates to the field of communication safety, and discloses a cascade decoding method suitable for data post-processing of a CV-QKD system. The invention fully combines the advantages of different code length coding technologies, and improves the error correction rate while ensuring the error correction success rate, thereby ensuring the overall performance of the CV-QKD system.
Description
Technical Field
The invention relates to the technical field of communication safety, in particular to a cascade decoding method suitable for data post-processing of a CV-QKD system.
Background
With the development of quantum computing technology, a classical cryptosystem based on computational complexity faces a significant potential safety hazard. Quantum Key Distribution (QKD) is a Key Distribution system based on the Quantum physical principle, has unconditional security, and has attracted extensive attention and research. Continuous variable Quantum Key Distribution (CV-QKD) adopts orthogonal components of an optical field as information carriers, most devices are universal to classical coherent optical communication, compatibility with a traditional optical communication network is good, and the continuous variable Quantum Key Distribution has a good development prospect. The current CV-QKD system is mainly realized based on GG02 protocol, namely Gaussian modulation coherent state transmission protocol, and a system transmitting end completes loading of Gaussian random variable key information by modulating two orthogonal components of a quantum state optical signal.
For the CV-QKD system, after weak quantum signals are transmitted through a long-distance optical fiber, the signal-to-noise ratio is very low, so that the error rate of original data of a transmitting party and a receiving party of key distribution is very high, and a consistent key can be obtained only through data post-processing. The rate and efficiency of the post-processing will greatly affect the overall performance of the CV-QKD system, and is a major bottleneck of the current CV-QKD system, wherein data negotiation error correction at a very low signal-to-noise ratio is the most critical.
In the CV-QKD system, information is carried on continuous variables, and the continuous variables are obtained by both legal communication parties after data screening instead of binary bits. Therefore, usually, a continuous variable is converted into a discrete form through a data negotiation algorithm, and then error correction is performed by using a specific channel coding based on the discrete form data, so that bit sequences of both communication parties are consistent.
At present, a multidimensional negotiation algorithm is generally adopted to convert continuous variables into discrete form data, and the multidimensional negotiation algorithm does not firstly quantize the continuous variable data into discrete values for error correction like the traditional method, but directly uses the continuous variables for negotiation. The core idea of multidimensional negotiation is to transform the variable space of non-uniform Gaussian distribution into the variable space of uniform distribution through mapping, and select the code word subspace with uniform distribution of prior probability in the uniform distribution space. Therefore, the random variables and the code word distribution are uniformly distributed, when both sides of the shared key transmit side information about the code word, extra related information quantity cannot be obtained, meanwhile, the correlation among original data can be fully utilized, and the problem of data discretization can be solved more ideally.
In the error correction stage of discrete form data, because the signal-to-noise ratio of data is extremely low, the conventional channel coding technology is no longer applicable, and the existing CV-QKD system generally adopts a multi-edge Low Density Parity Check (LDPC) to perform error correction coding. The multi-edge LDPC code is proposed for the first time in 2004 and has good error correction performance under various transmission lengths and code rates. In the CV-QKD system, on one hand, the data coordination efficiency can be ensured by designing a polygonal LDPC error correction matrix with a low code rate, so that the safe code rate of the system is ensured; on the other hand, by increasing the error correction code length of the multi-edge LDPC matrix, more code word information can be comprehensively acquired, so that the error correction success rate is increased.
The overall flow of the CV-QKD system is shown in FIG. 1. Firstly, a sending end sends quantum signal light to a receiving end through a quantum channel based on a signal sending module, and the receiving end detects and receives the quantum signal light based on a signal receiving module. Then the sending end and the receiving end enter a data post-processing stage, and complete data post-processing by performing partial data interaction on a classical channel, so that the sending end and the receiving end acquire a consistent final key. And finally, the sending end and the receiving end respectively output the final key to respective key application service modules for subsequent key storage, information encryption and the like.
The current data post-processing flow is shown in fig. 2, and mainly comprises the following steps of basis comparison, parameter estimation, data negotiation, error correction, private key amplification and the like:
base comparison: firstly, a receiving terminal sends measurement Base data Base adopted in signal detection to a sending terminal through a classical channel, the sending terminal receives the measurement Base data Base, then consistent orthogonal components are selected according to the Base, and the sending terminal and the receiving terminal respectively acquire original data x and y after Base comparison.
Parameter estimation: then, the sending end and the receiving end need to perform parameter estimation to calculate part of key parameters in the key distribution process, and the parameter estimation can be performed at the sending end or the receiving end. In fig. 2, taking parameter estimation at the receiving end as an example, the transmitting end randomly selects a part of data x _ para from original data x, then sends x _ para and a corresponding data position pos to the receiving end, the receiving end receives the data at a corresponding position selected from y according to pos, then performs parameter estimation by combining x _ para, calculates parameters such as SNR, cross-noise ξ, and security code rate k, and sends the parameter estimation result to the transmitting end through a classical channel. Since the data for parameter estimation is exposed on the classical channel, the transmitting end and the receiving end need to eliminate the data for parameter estimation respectively, and generate data x1 and y1 respectively to enter the subsequent data negotiation step.
Data negotiation: the sending end and the receiving end convert continuous data into discrete data through a certain negotiation algorithm (including but not limited to multidimensional negotiation and sliced negotiation). The data negotiation may be initiated by a sending end or a receiving end, and fig. 2 is initiated by the receiving end, which is also called reverse coordination (initiated by the sending end, the forward coordination is achieved), and is generally implemented by using a multidimensional negotiation algorithm at present. The receiving end firstly generates a binary random sequence U with the same length as y1, then calculates a packet module length Mod and a spherical coordinate alpha based on a multi-dimensional negotiation algorithm, and sends the packet module length Mod and the spherical coordinate alpha to the sending end through a classical channel. After receiving the Mod and the α, the transmitting end calculates data V based on a multidimensional negotiation algorithm in combination with x1, and the data V can be equivalent to data obtained by superimposing BPSK coding symbols of the random sequence U on noise. After data negotiation, conversion from continuous variable data to discrete form data is completed, and error code correction can be performed.
Error correction of the bit error: the initiator of error correction is consistent with that of data negotiation, so that fig. 2 is initiated from the receiving end, and at present, a multilateral LDPC code (also may be a turbo code or the like) is generally used for error correction decoding. The receiving end calculates a syndrome s based on the multi-edge LDPC error correction matrix and the random sequence U, and sends the syndrome s to the sending end through a classical channel. And after the transmitting end receives s, decoding and correcting V in the hands based on the s and the error correction matrix, and gradually reducing the error number to 0 through continuous iterative decoding to finally obtain a bit sequence U consistent with the receiving end.
Amplifying a private key: and the transmitting end and the receiving end compress the bit sequence according to the safety code rate k calculated in the parameter estimation, and finally obtain a consistent final safety key.
The data negotiation and error correction are very important for the performance of the CV-QKD system, the data negotiation problem can be better solved by adopting a multidimensional data coordination algorithm at present, but the multi-edge LDPC error correction decoding technology which is commonly adopted in the error correction process has certain defects. In the error correction decoding process of the multi-edge LDPC code, a single long code length code is often adopted for decoding, the error code quantity is reduced very fast in the initial decoding stage, however, when the error code quantity is smaller than a certain threshold value, the reduction speed is rapidly reduced, finally, few error codes can be successfully corrected after repeated iteration for many times, even the situation that the error can not be corrected after repeated iteration occurs, the error correction decoding speed is obviously reduced, and the overall performance of the CV-QKD system is obviously influenced.
Disclosure of Invention
Aiming at the problems that in the current CV-QKD system data post-processing, the iteration times are obviously increased due to few error codes in the iteration process when the multi-edge type LDPC codes are used for error correction, and the error correction decoding fails within the specified iteration times, the invention provides a cascade decoding method suitable for CV-QKD system data post-processing.
The invention relates to a cascade decoding method suitable for CV-QKD system data post-processing, which adopts a mode of combining long code length coding with medium and short code length coding, firstly utilizes the long code length coding to correct errors so as to quickly reduce the error quantity to be within a preset threshold value within less iteration times, then reduces the length of error correction coding, regroups all bits, verifies the code words grouped by a transmitting party and a receiving party based on a verification function, corrects all errors by adopting the medium and short code length coding after the code words with inconsistent verification results are grouped, and finishes decoding.
Further, the error correction by using the long code length code comprises the following steps:
aiming at the discrete form data V and U of the transmitting end and the receiving end after base comparison, parameter estimation and multidimensional negotiation, code word grouping is carried out by using a longer code length L1, and the transmitting end obtains V1,V2,...,VNThe receiving end obtains U1,U2,...,UNWhere N is L/L1, and L is the total length of the sender and receiver data;
for codeword grouping ViAnd Ui1,2, 3., N, in the case of reverse coordination, the transmitting end and the receiving end select an error correction coding technique suitable for a long code length, wherein the error correction coding technique includes a multi-edge type low density parity check; the receiving end then groups U based on the code wordiAnd an error correction matrix H for calculating the syndrome s of the current codeword packetiAnd sends it to the sending end.
Further, the step of reducing the number of errors to be within the preset threshold value includes the following steps:
syndrome s of current code word packet received by transmitting endiThen, the initial error number Err0 is counted according to the initialized likelihood ratio obtained after the multidimensional negotiation, and then the code word group V is based oniError correction matrix H and syndrome siStarting BP iterative decoding; after each iteration decoding with fixed round number, counting the residual error number, and stopping decoding when the error number is lower than a preset threshold value; after stopping decoding, the sending end obtains a temporary code word WiIf the number of remaining errors is 0, then WiAnd UiAre consistent; if the number of remaining errors is not 0, then WiAnd UiAre inconsistent and require subsequent concatenated decoding.
Further, the reducing the length of the error correction code and regrouping all the bits includes the following steps:
the transmitting end and the receiving end combine all code word groups with the residual error number not being 0 into sequences W ' and U ', the sequence length is L ', the code word groups are carried out again by using the shorter code length L2, and the transmitting end obtains V1,V2,...,VMThe receiving end obtains U1,U2,...,UMWherein M is L'/L2.
Further, the checking the code words of the both sending and receiving party groups based on the check function, and adopting the middle and short code length coding error correction to the code word groups with inconsistent check results, includes the following steps:
grouping V for code words after regroupingjAnd UjJ 1,2, 3.. times.m, the receiving end calculates a codeword packet UjCheck function value c ofjAnd c isjSending the data to a sending end; the sending end selects the same check function to calculate the code word group VjResult of (a) tj；
Sending end decision tjAnd cjWhether the codes are equal or not, if so, the temporary code word W obtained by the sending end is indicatedjAnd UjThe consistency is realized, and the second-level error correction decoding is not needed; if not, then W is indicatedjAnd UjIf the codes are inconsistent, the sending end and the receiving end select a medium-short code length code to carry out second-stage error correction decoding, and finally the sending end obtains a code word U consistent with the receiving endj。
Further, the base alignment comprises the following steps:
the receiving end sends the measurement Base data Base adopted in signal detection to the sending end through a classical channel, and after the sending end receives the measurement Base data Base, the sending end selects consistent orthogonal components according to the measurement Base data Base to obtain original data x and y.
Further, the parameter estimation can be performed at a transmitting end or a receiving end, and if the parameter estimation is performed at the receiving end, the parameter estimation includes the following steps:
the method comprises the steps that a sending end randomly selects a part of data x _ para from original data x, then sends the x _ para and corresponding data positions pos to a receiving end, the receiving end receives the data of corresponding positions selected from the original data y according to the data positions pos, then parameter estimation is carried out by combining the x _ para, key parameters including signal-to-noise ratio (SNR), excessive noise xi, safe code rate k and the like are calculated, and parameter estimation results are sent to the sending end through a classical channel; the transmitting end and the receiving end eliminate the data used for parameter estimation respectively, and generate data x1 and y1 respectively.
Further, the multidimensional negotiation can be initiated by a sending end or a receiving end, and if the multidimensional negotiation is initiated by the receiving end, the multidimensional negotiation comprises the following steps:
the receiving end firstly generates a binary random sequence U with the same length as the data y1, then calculates a packet module length Mod and a spherical coordinate alpha based on a multi-dimensional negotiation algorithm, and sends the packet module length Mod and the spherical coordinate alpha to the sending end through a classical channel; after receiving the Mod and the α, the transmitting end calculates data V based on a multidimensional negotiation algorithm in combination with the data x1, and the data V can be equivalent to data obtained by superimposing BPSK coding symbols of the random sequence U on noise.
Further, the medium-short code length code comprises a BCH code and an RS code.
Further, the check function includes cyclic redundancy check, CRC, and hash function check.
The invention has the beneficial effects that:
the cascade decoding method provided by the invention firstly corrects most errors in less iteration times by using long code length coding, then reduces the length of error correction coding, adopts more appropriate medium and short code length coding error correction aiming at code word groups still having errors, fully combines the advantages of different code length coding technologies, ensures the success rate of error correction and simultaneously improves the error correction rate, thereby ensuring the overall performance of the CV-QKD system.
Drawings
FIG. 1 is an overall flow diagram of the CV-QKD system;
FIG. 2 is a flowchart of CV-QKD system data post-processing;
FIG. 3 is a flowchart of a concatenated decoding method of the present invention.
Detailed Description
In order to more clearly understand the technical features, objects, and effects of the present invention, specific embodiments of the present invention will now be described. It should be understood that the detailed description and specific examples, while indicating the preferred embodiment of the invention, are intended for purposes of illustration only and are not intended to limit the scope of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present invention without making any creative effort, shall fall within the protection scope of the present invention.
The embodiment provides a cascade decoding method suitable for CV-QKD system data post-processing, which adopts a mode of combining long code length coding and medium and short code length coding, firstly corrects errors by using the long code length coding so as to quickly reduce the number of errors to be within a preset threshold value within a few iteration times, then reduces the length of error correction coding, regroups all bits, verifies the code words grouped by a transmitting party and a receiving party based on a verification function, corrects all errors by adopting the medium and short code length coding for code words with inconsistent verification results, and finishes decoding. Therefore, the advantages of coding technologies with different code lengths are fully combined, the error correction rate is improved while the error correction success rate is ensured, and the overall performance of the CV-QKD system is ensured.
In a preferred embodiment of the present invention, as shown in fig. 3, the method for cascade decoding includes the following specific steps:
step one, aiming at discrete form data V and U of a transmitting end and a receiving end after base comparison, parameter estimation and multidimensional negotiation, code word grouping is carried out by a longer code length L1, and the transmitting end obtains V1,V2,...,VNThe receiving end obtains U1,U2,...,UNWhere N is L/L1, and L is the total length of the sender and receiver data;
for codeword grouping ViAnd UiN, in the case of reverse coordination, the transmitting end and the receiving end select an error correction coding technique Code1 suitable for a long Code length, including but not limited to a multi-edge type LDPC Code; the receiving end then groups U based on the code wordiAnd an error correction matrix H for calculating the syndrome s of the current codeword packetiAnd sending to the sending end;
step two, the transmitting end receives the syndrome s of the current code word groupiThen, the initial error number Err0 is counted according to the initialized likelihood ratio obtained after the multidimensional negotiation, and then the code word group V is based oniError correction matrix H and syndrome siStarting BP iterative decoding; counting the residual error number after each iteration decoding with fixed round number, and stopping decoding when the error number is lower than a preset threshold value (for example, 0.1 × Err0), wherein the specific selection of the preset threshold value is related to the overall parameter setting of the CV-QKD system; after stopping decoding, the sending end obtains a temporary code word WiIf the number of remaining errors is 0, then WiAnd UiAre consistent; if the number of remaining errors is not 0, then WiAnd UiIf the data is inconsistent, subsequent cascade decoding is required;
step three, the transmitting end and the receiving end combine all code word groups with the residual error number not being 0 into sequences W ' and U ', the sequence length is L ', the code word groups are carried out again by using the shorter code length L2, and the transmitting end obtains V1,V2,...,VMThe receiving end obtains U1,U2,...,UMWherein M ═ L'/L2;
grouping V for code words after regroupingjAnd UjJ 1,2, 3.. times.m, the receiving end calculates a codeword packet UjCheck function value c ofjAnd c isjSending to the sending end, wherein the check function includes but is not limited to CRC32, AES, MD 5; the sending end selects the same check function to calculate the code word group VjResult of (a) tj；
Step four, the sending end judges tjAnd cjWhether the data are equal or not, if so, the sending end is indicated to be obtainedTemporary code word WjAnd UjThe consistency is realized, and the second-level error correction decoding is not needed; if not, then W is indicatedjAnd UjIf the codes are inconsistent, the transmitting end and the receiving end select a Code2 with a medium-short Code length for secondary error correction decoding, wherein the medium-short Code length codes include but are not limited to BCH codes, RS codes and the like, and the residual error amount is less after error correction of Code1, so that the secondary error correction decoding can be easily realized, and finally the transmitting end obtains a Code U consistent with the receiving endj。
After all code word groups are executed, the sending end and the receiving end have completely consistent code word data, and the integral error correction decoding is realized.
In a preferred embodiment of the invention, the base alignment comprises the steps of:
the receiving end sends the measurement Base data Base adopted in signal detection to the sending end through a classical channel, and after the sending end receives the measurement Base data Base, the sending end selects consistent orthogonal components according to the measurement Base data Base to obtain original data x and y.
In a preferred embodiment of the present invention, the parameter estimation can be performed at the transmitting end or the receiving end, and if the parameter estimation is performed at the receiving end, the parameter estimation includes the following steps:
the method comprises the steps that a sending end randomly selects a part of data x _ para from original data x, then sends the x _ para and corresponding data positions pos to a receiving end, the receiving end receives the data of corresponding positions selected from the original data y according to the data positions pos, then parameter estimation is carried out by combining the x _ para, key parameters including signal-to-noise ratio (SNR), excessive noise xi, safe code rate k and the like are calculated, and parameter estimation results are sent to the sending end through a classical channel; since the data for parameter estimation is exposed on the classical channel, the transmitting end and the receiving end need to eliminate the data for parameter estimation respectively, and generate data x1 and y1 respectively.
In a preferred embodiment of the present invention, the multidimensional negotiation can be initiated by a sending end or a receiving end, and if initiated by the receiving end, the multidimensional negotiation includes the following steps:
the receiving end firstly generates a binary random sequence U with the same length as the data y1, then calculates a packet module length Mod and a spherical coordinate alpha based on a multi-dimensional negotiation algorithm, and sends the packet module length Mod and the spherical coordinate alpha to the sending end through a classical channel; after receiving the Mod and the α, the transmitting end calculates data V based on a multidimensional negotiation algorithm in combination with the data x1, and the data V can be equivalent to data obtained by superimposing BPSK coding symbols of the random sequence U on noise. After multi-dimensional negotiation, the conversion from continuous variable data to discrete form data is completed, and error correction can be carried out.
The foregoing is illustrative of the preferred embodiments of this invention, and it is to be understood that the invention is not limited to the precise form disclosed herein and that various other combinations, modifications, and environments may be resorted to, falling within the scope of the concept as disclosed herein, either as described above or as apparent to those skilled in the relevant art. And that modifications and variations may be effected by those skilled in the art without departing from the spirit and scope of the invention as defined by the appended claims.
Claims (10)
1. A cascade decoding method suitable for CV-QKD system data post-processing is characterized in that a long code length coding and a medium-short code length coding are combined, firstly, long code length coding is used for error correction, so that the error quantity is quickly reduced to a preset threshold value within a few iteration times, then, the length of error correction coding is reduced, all bits are regrouped, code words grouped by a transmitting party and a receiving party are verified based on a verification function, code words with inconsistent verification results are grouped, medium-short code length coding is used for error correction, all errors are finally corrected, and decoding is completed.
2. The concatenated decoding method for CV-QKD system data post-processing according to claim 1, wherein said error correction using long code length coding comprises the following steps:
aiming at the discrete form data V and U of the sending end and the receiving end after base comparison, parameter estimation and multidimensional negotiation, code word grouping is carried out by using a longer code length L1, and the sending end obtains V1,V2,...,VNThe receiving end obtains U1,U2,...,UNWhere N is L/L1, and L is the total length of the sender and receiver data;
for codeword grouping ViAnd Ui1,2, 3., N, in the case of reverse coordination, the transmitting end and the receiving end first select an error correction coding technique suitable for a long code length, the error correction coding technique including a multi-sided low density parity check; the receiving end then groups U based on the code wordiAnd an error correction matrix H for calculating the syndrome s of the current codeword packetiAnd sends it to the sending end.
3. The cascade decoding method for CV-QKD system data post-processing according to claim 2, wherein said reducing the number of errors to within a preset threshold value comprises the steps of:
syndrome s of current code word packet received by transmitting endiThen, the initial error number Err0 is counted according to the initialized likelihood ratio obtained after the multidimensional negotiation, and then the code word group V is based oniError correction matrix H and syndrome siStarting BP iterative decoding; after each iteration decoding with fixed round number, counting the residual error number, and stopping decoding when the error number is lower than a preset threshold value; after stopping decoding, the sending end obtains a temporary code word WiIf the number of remaining errors is 0, then WiAnd UiAre consistent; if the number of remaining errors is not 0, then WiAnd UiAre inconsistent and require subsequent concatenated decoding.
4. The concatenated decoding method for CV-QKD system data post-processing according to claim 3, wherein said reducing the length of error correction coding, and regrouping all bits, comprises the following steps:
the transmitting end and the receiving end combine all code word groups with the residual error number not being 0 into sequences W ' and U ', the sequence length is L ', the code word groups are carried out again by using the shorter code length L2, and the transmitting end obtains V1,V2,...,VMThe receiving end obtains U1,U2,...,UMWherein M is L'/L2.
5. The cascade decoding method suitable for CV-QKD system data post-processing according to claim 4, wherein said checking function is used to check code words grouped by both the transmitter and the receiver, and for code word groups with inconsistent checking results, medium and short code length coding error correction is used, comprising the steps of:
grouping V for code words after regroupingjAnd UjJ 1,2, 3.. times.m, the receiving end calculates a codeword packet UjCheck function value c ofjAnd c isjSending the data to a sending end; the sending end selects the same check function to calculate the code word group VjResult of (a) tj；
Sending end decision tjAnd cjWhether the codes are equal or not, if so, the temporary code word W obtained by the sending end is indicatedjAnd UjThe consistency is realized, and the second-level error correction decoding is not needed; if not, then W is indicatedjAnd UjIf the codes are inconsistent, the sending end and the receiving end select a medium-short code length code to carry out second-stage error correction decoding, and finally the sending end obtains a code word U consistent with the receiving endj。
6. The cascade decoding method for CV-QKD system data post-processing according to claim 2, wherein the base comparison comprises the following steps:
the receiving end sends the measurement Base data Base adopted in signal detection to the sending end through a classical channel, and after the sending end receives the measurement Base data Base, the sending end selects consistent orthogonal components according to the measurement Base data Base to obtain original data x and y.
7. The concatenated decoding method for CV-QKD system data post-processing according to claim 6, wherein the parameter estimation can be performed at a transmitting end or a receiving end, and if performed at the transmitting end, the parameter estimation includes the following steps:
the method comprises the steps that a sending end randomly selects a part of data x _ para from original data x, then sends the x _ para and corresponding data positions pos to a receiving end, the receiving end receives the data of corresponding positions selected from the original data y according to the data positions pos, then parameter estimation is carried out by combining the x _ para, key parameters including signal-to-noise ratio (SNR), excessive noise xi, safe code rate k and the like are calculated, and parameter estimation results are sent to the sending end through a classical channel; the transmitting end and the receiving end eliminate the data used for parameter estimation respectively, and generate data x1 and y1 respectively.
8. The concatenated decoding method for CV-QKD system data post-processing according to claim 7, wherein the multidimensional negotiation can be initiated by a transmitting end or a receiving end, and if initiated by the receiving end, the multidimensional negotiation includes the following steps:
the receiving end firstly generates a binary random sequence U with the same length as the data y1, then calculates a packet module length Mod and a spherical coordinate alpha based on a multi-dimensional negotiation algorithm, and sends the packet module length Mod and the spherical coordinate alpha to the sending end through a classical channel; after receiving the Mod and the α, the transmitting end calculates data V based on a multidimensional negotiation algorithm in combination with the data x1, and the data V can be equivalent to data obtained by superimposing BPSK coding symbols of the random sequence U on noise.
9. The concatenated decoding method for CV-QKD system data post-processing according to claim 1, wherein said medium-short code length coding includes BCH codes and RS codes.
10. The cascaded decoding method for CV-QKD system data post-processing according to claim 1, wherein the check function includes Cyclic Redundancy Check (CRC) and hash function check.
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