Multi-attribute quantum satellite switching strategy based on quantum genetic algorithm

Abstract

The embodiment of the invention relates to a multi-attribute quantum satellite switching strategy based on a quantum genetic algorithm. The multi-attribute quantum satellite switching strategy is characterized in that comprehensive weighting is carried out according to three attributes of a channel error rate among quantum satellite particles, a reciprocal of time delay and a channel establishment rate to establish a fitness function; according to the fitness function, a multi-attribute quantum satellite switching strategy of a quantum genetic algorithm is utilized, service parameters provided by a plurality of quantum satellites are synthesized, and the quantum satellite with the optimal switching comprehensive performance is selected; according to the embodiment of the invention, comprehensive weighting is carried out according to three attributes of the channel error rate, the transmission time delay and the channel establishment rate among quantum satellite particles to establish the fitness function, and the quantum satellite with the best performance is selected according to the fitness function by using a multi-attribute quantum satellite switching strategy of the quantum genetic algorithm. The call blocking rate and the handover failure rate are reduced, good stability is kept, and the load of the quantum satellite is averaged.

Description

Technical Field

[0001] The present disclosure relates to the field of communication security technology, and in particular to a multi-attribute quantum satellite switching strategy based on quantum genetic algorithm. Background Art

[0002] Among the many advances in quantum information technology, quantum communication systems have received special attention. Since there are many key quantum features in quantum signals, such as superposition, interference, and entanglement, quantum communication has high security and high anti-interference capabilities, which is expected to fundamentally innovate information transmission and encryption modes and promote the development of scalable quantum networks. With quantum satellites as the link, a secure communication network has been built worldwide. Based on a single optical photon, quantum key distribution technology is used to solve security issues in satellite networks, so that the optical signals sent between the ground and the satellite can cover a longer distance than similar ground links, which has important research significance.

[0003] With the development of low-Earth orbit quantum satellites, the number of ground gateways will also increase. For ground stations, there are more and more situations where there are multiple quantum satellites to choose from. Therefore, it is very necessary to study the access selection technology under the coverage of multiple quantum satellites to achieve communication continuity. Theoretically, the change law of various parameters such as bit error rate and survivability of satellite quantum communication systems at different altitude angles was studied, and the feasibility of using the setting angle size as a switching judgment was demonstrated. However, this method uses a single attribute as the criterion for switching judgment, sacrificing the advantages of other attributes and limiting the adaptability of satellite systems in different application scenarios.

[0004] Therefore, it is necessary to propose a solution to improve one or more problems existing in the above-mentioned related technical solutions.

[0005] It should be noted that the information disclosed in the above background technology section is only used to enhance the understanding of the background of the present disclosure, and therefore may include information that does not constitute the prior art known to ordinary technicians in the field. Summary of the invention

[0006] The embodiment of the present disclosure provides a multi-attribute quantum satellite switching strategy based on a quantum genetic algorithm, comprising the following steps:

[0007] Establish a communication system model for quantum satellites;

[0008] According to the communication of quantum satellite, the three attributes of channel bit error rate, transmission delay and channel establishment rate between particles of quantum satellite are comprehensively weighted to establish fitness function;

[0009] According to the fitness function, the quantum satellite switching strategy with multiple attributes of quantum genetic algorithm is used to select the quantum satellite with the best switching comprehensive performance;

[0010] Through simulation experiments, the multi-attribute quantum satellite switching strategy using quantum genetic algorithm based on the fitness function is verified to reduce the switching failure rate and the blocking rate of new calls.

[0011] In an exemplary embodiment of the present disclosure, the fitness function is expressed as:

[0012] f(x)=αQ+βK+γV (1)

[0013] Among them, Q represents the inverse of the channel bit error rate, K represents the inverse of the transmission delay, V represents the channel establishment rate, α is the weighting coefficient of the quantum bit error rate, β is the weighting coefficient of the transmission delay, γ is the weighting coefficient of the channel establishment rate, and α+β+γ=1 is satisfied.

[0014] In an exemplary embodiment of the present disclosure, the expression of the channel bit error rate is:

[0015]

[0016] Where W(λ) is the background radiation spectrum, θ r is the receiver field of view, τ is the time window, n is the number of detectors, μ is the average number of photons per pulse, T cha is the transmission rate of the quantum channel, P acq is the single photon capture probability, T app is the transmission rate of the system device, η det is the quantum efficiency of the single-photon detector, F mea is the measurement factor.

[0017] In an exemplary embodiment of the present disclosure, the expression of the transmission delay is:

[0018]

[0019] Where T' is the average time of Bell basis measurement between nodes, T" is the wireless transmission delay between nodes, and m is the number of nodes in the intermediate satellite transmission.

[0020] In an exemplary embodiment of the present disclosure, the expression of the channel establishment rate is:

[0021] V(F)=f max ·P g (F) (4)

[0022] Among them, V represents the channel establishment rate, F is the fidelity that the communication process needs to meet, and P g (F) is the probability of successfully meeting the fidelity, the maximum frequency f max=MC / 4d, M is the storage space value of entangled photons, M=4[df / c], f is the operating frequency of the entangled photon pair, d is the distance between the two nodes, C is the speed of light, and the square brackets are rounding functions.

[0023] In an exemplary embodiment of the present disclosure, the algorithm steps of the multi-attribute quantum satellite switching strategy using the quantum genetic algorithm according to the fitness function are:

[0024] According to the service request, the parameters of the three attributes of the channel bit error rate, transmission delay and channel establishment rate between particles of each quantum satellite are obtained, and the fitness function is applied to each individual in the initial population Q(t0) to measure and calculate, and the corresponding definite solution P(t0) is obtained;

[0025] Perform fitness evaluation on each of the determined solutions P(t0), and record the optimal individual and the corresponding fitness;

[0026] According to the fitness evaluation results, it is determined whether there is an optimal quantum satellite for switching. If there is an optimal quantum satellite for switching, the switching is completed. If there is no optimal quantum satellite for switching, a new population Q(t) is generated and the calculation continues.

[0027] In the population Q(t), each individual in the population is measured and calculated according to the fitness function to obtain the corresponding definite solution P(t), and the fitness of each definite solution P(t) is evaluated;

[0028] Use the quantum rotating door U(t) to change the individuals and obtain a new population Q(t+1);

[0029] Record the best individual and the corresponding fitness;

[0030] According to the fitness evaluation results, it is judged whether there is an optimal quantum satellite for switching. If there is an optimal quantum satellite for switching, the switching is completed. If there is no optimal quantum satellite for switching, the number of iterations t is increased by 1 and the calculation is continued.

[0031] The present disclosure proposes a multi-attribute quantum satellite switching strategy based on a quantum genetic algorithm, which can include the following beneficial effects: establishing a fitness function by comprehensively weighting the three attributes of the channel bit error rate, the inverse of the delay, and the channel establishment rate between quantum satellite particles; selecting a quantum satellite with the best comprehensive switching performance by using the multi-attribute quantum satellite switching strategy of the quantum genetic algorithm according to the fitness function, so that all performance indicators of the ground station during switching can be kept optimal, reducing the call blocking rate and the inter-zone switching failure rate, maintaining good stability, and averaging the load of the quantum satellite. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] The accompanying drawings herein are incorporated into the specification and constitute a part of the specification, illustrate embodiments consistent with the present disclosure, and together with the specification are used to explain the principles of the present disclosure. Obviously, the accompanying drawings described below are only some embodiments of the present disclosure, and for ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without creative work.

[0033] Figure 1 A schematic diagram showing the steps of a multi-attribute quantum satellite switching strategy based on a quantum genetic algorithm in an exemplary embodiment of the present disclosure;

[0034] Figure 2 A schematic diagram showing a scenario of ground station-satellite switching in a low-orbit quantum satellite communication system in an exemplary embodiment of the present disclosure;

[0035] Figure 3 A schematic diagram of a six-orbit Iridium satellite system in an exemplary embodiment of the present disclosure is shown;

[0036] Figure 4 A schematic diagram showing the relationship between the zenith angle and the bit error rate under the influence of background light (daytime) in an exemplary embodiment of the present disclosure;

[0037] Figure 5 A schematic diagram of a quantum satellite switching strategy process based on a quantum genetic algorithm with multiple attributes in an exemplary embodiment of the present disclosure is shown;

[0038] Figure 6 A comparison diagram of the quantum genetic algorithm and the classical genetic algorithm model in the simulation experiment disclosed in the present invention is shown;

[0039] Figure 7 A schematic diagram showing the satellite network call blocking rate in the simulation experiment disclosed in the present invention is shown;

[0040] Figure 8 A schematic diagram showing the failure rate of satellite network switching in the simulation experiment disclosed in the present invention is shown; DETAILED DESCRIPTION

[0041] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in a variety of forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that the disclosure will be more comprehensive and complete and to fully convey the concepts of the example embodiments to those skilled in the art. The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.

[0042] In addition, the accompanying drawings are only schematic illustrations of the present disclosure and are not necessarily drawn to scale. The same reference numerals in the figures represent the same or similar parts, and their repeated description will be omitted. Some of the block diagrams shown in the accompanying drawings are functional entities and do not necessarily correspond to physically or logically independent entities. These functional entities can be implemented in software form, or implemented in one or more hardware modules or integrated circuits, or implemented in different networks and / or processor devices and / or microcontroller devices.

[0043] This example implementation provides a multi-attribute quantum satellite switching strategy based on quantum genetic algorithm, such as Figure 1 As shown, the following steps may be included:

[0044] Step S101: Establish a communication system model of a quantum satellite.

[0045] Step S102: A fitness function is established by comprehensively weighting the three attributes of the channel bit error rate, transmission delay and channel establishment rate between particles of the quantum satellite according to the communication of the quantum satellite.

[0046] Step S103: Using the multi-attribute quantum satellite switching strategy of the quantum genetic algorithm according to the fitness function, a quantum satellite with the best switching comprehensive performance is selected.

[0047] Step S104: verifying through simulation experiments that the multi-attribute quantum satellite switching strategy using the quantum genetic algorithm according to the fitness function reduces the switching failure rate and reduces the blocking rate of new calls.

[0048] In the embodiment of the present disclosure, a multi-attribute quantum satellite switching strategy based on a quantum genetic algorithm is proposed, which can include the following beneficial effects: a fitness function is established by comprehensively weighting the three attributes of the channel bit error rate, the inverse of the delay, and the channel establishment rate between quantum satellite particles; a quantum satellite with the best comprehensive switching performance is selected according to the multi-attribute quantum satellite switching strategy of the quantum genetic algorithm based on the fitness function, so that various performance indicators of the ground station during switching can be kept optimal, the call blocking rate and the inter-zone switching failure rate are reduced, and good stability is maintained, and the load of the quantum satellite is averaged.

[0049] The following describes each step of the above method in this exemplary embodiment in more detail.

[0050] Step S101: Establish a communication system model of a quantum satellite.

[0051] Specific: such as Figure 2As shown in the figure, in the ground station-satellite switching scenario of the low-orbit quantum satellite communication system, when a new switching star is selected, the switching generally only determines the next switching star based on a single attribute or multiple attributes. However, the selected path is only an optimal solution and cannot guarantee that all communication times are optimal, thus affecting the service quality of the system.

[0052] Each satellite irradiates the ground with multiple beams. The Iridium mobile satellite communication system consists of 6 vertical orbits with an altitude of 780 km. Figure 3 As shown, there are 11 main satellites on each vertical orbit, each satellite has 48 beams, and its coverage area diameter is 2,800 kilometers. In the quantum satellite communication system, the Iridium mobile satellite communication system is used to perform quantum genetic algorithm for multi-objective optimization path screening.

[0053] Step S102: Establish a fitness function by performing comprehensive weighting according to the three attributes of the channel bit error rate, the inverse of the delay and the channel establishment rate between particles of the quantum satellite.

[0054] Specifically: In the low-orbit quantum satellite system, for terminal inter-satellite switching, it is first necessary to define the goal of the fitness function to maximize the performance of the system, that is, to minimize the bit error rate, minimize the delay, and maximize the channel establishment rate. The channel error rate switching selection means that the currently selected satellite has the best call quality; the transmission delay switching selection means that the selected satellite currently causes the least call interference; the channel establishment rate is used as the switching criterion, indicating that the selected satellite has the largest capacity in the current communication system. Therefore, when selecting multiple attributes for switching selection, the satellite with a smaller channel error rate and delay and a higher channel establishment rate should be selected for switching.

[0055] The inverse of the satellite's channel bit error rate, the inverse of the delay, and the channel establishment rate are used as the objective functions of the three attributes, and comprehensive weighting is performed to select the quantum satellite access that is most beneficial to the current situation. When a larger fitness function is selected, it means that the selected satellite has the best switching performance at present. The fitness function established based on the three attributes of channel bit error rate, delay, and channel establishment rate is:

[0056] f(x)=αQ+βK+γV (1)

[0057] Among them, Q represents the inverse of the channel bit error rate, K represents the inverse of the transmission delay, V represents the channel establishment rate, α is the weighting coefficient of the quantum bit error rate, β is the weighting coefficient of the transmission delay, γ is the weighting coefficient of the channel establishment rate, and α+β+γ=1 is satisfied.

[0058]

[0059] Among them, α is the weighted coefficient of quantum bit error rate, β is the weighted coefficient of transmission delay, γ is the weighted coefficient of channel establishment rate, and α+β+γ=1 is satisfied. It reflects the criterion for switching and is used to control the importance of different indicators to fitness. If different systems have different priority requirements for channel bit error rate, delay, and channel establishment rate, the purpose of dynamic adjustment can be achieved by adjusting the values ​​of α, β, and γ. The values ​​are (α=0.3, β=0.3, γ=0.4). The larger the value of the fitness function f(x), the better the comprehensive performance of the satellite and the greater the possibility of user's first choice of access, and vice versa.

[0060] According to the B92 quantum key distribution system, during the communication between low-orbit satellites and the ground, the quantum bit error rate refers to the ratio of the number of received error bits to the total number of bits, usually expressed as QBER. Its mathematical expression is:

[0061]

[0062] In the formula, R sift is the quantum bit rate after data screening (including positive and error codes), R error is the quantum bit rate of bit error.

[0063] For satellite-to-ground quantum key distribution, the quantum channel transmission rate can be expressed as:

[0064] T cha =T0 secζ (5)

[0065] Where ζ is the zenith angle from the ground terminal to the satellite, and T0 is the atmospheric transmission rate at the zenith (ζ = 0°). Based on the fundamental mode Gaussian beam, the single photon capture probability can be expressed as:

[0066]

[0067] In the formula, is the transmitter pointing error, θ0 is the far-field divergence angle of the fundamental mode Gaussian beam, L is the link distance between the transmitter and the receiver, and d is the receiver antenna aperture.

[0068] In a free-space optical environment, background radiation can cause background photons to reach the receiver, resulting in bit errors. For satellite-to-ground quantum key distribution, the quantum bit error rate caused by background light is:

[0069]

[0070] Where W(λ) is the background radiation spectrum, θ r is the receiver field of view, τ is the time window, n is the number of detectors, μ is the average number of photons per pulse, T chais the transmission rate of the quantum channel, P acq is the single photon capture probability, T app is the transmission rate of the system device, η det is the quantum efficiency of the single-photon detector, F mea is the measurement factor (for B92 protocol, F mea =1 / 4).

[0071] Table 1 Channel bit error rate parameter settings

[0072]

[0073] For quantum key distribution between a low-orbit quantum satellite and a ground station at an orbital altitude of 780 km, the following simulation is performed:

[0074] like Figure 4 As shown, the x-axis is the zenith angle ζ between the ground station and the quantum satellite, and the y-axis is the quantum bit error rate QBER. It can be seen from the figure that there is a certain relationship between the quantum bit error rate caused by background light during the day and the zenith angle. When the zenith angle is 0 degrees, the quantum bit error rate reaches the minimum value. Therefore, in order to improve the reliability of the quantum communication system, an environment with a larger zenith angle should be selected for communication as much as possible. When the zenith angle ζ>0.6rad, the QBER value drops rapidly; as the zenith angle ζ<0.6, the QBER value changes more slowly, and there is no obvious fluctuation. It can be seen that the zenith angle has a greater impact on the QBER value when the arc is larger. Therefore, quantum satellite switching can achieve the purpose of reducing the bit error rate of quantum communication by adjusting the zenith angle of the quantum satellite.

[0075] The intersatellite transmission delay reflects the degree of communication interference in the process of satellite-to-ground quantum satellite communication. As the transmission delay increases, the performance of the system will also deteriorate. In the construction of a double-ended entangled quantum satellite network, the quantum information transmission delay from the source node satellite to the target node satellite is:

[0076]

[0077] Among them, T' is the average time of Bell basis measurement between nodes, T" is the wireless transmission delay between nodes, and m is the number of nodes in the intermediate satellite transmission. The larger the T value, the more resources the satellite consumes. The time of quantum measurement is 1-5ns, but because the magnitude difference between the two is very large, in wireless communication, the communication delay of a single node is usually only 10-50ms, so the quantum measurement time can be ignored. That is, T'=1-5ns, T"=10-50ms. The establishment rate of the quantum channel refers to the speed of establishing a quantum entangled pair between two quantum communication nodes. The channel establishment rate between a quantum satellite and an earth station based on entangled particles is defined as:

[0078] v(F)=f max ·P g (F) (9)

[0079] In the formula, f is the operating frequency of the entangled photon pair, which is related to the storage space value M of the entangled photons, M = 4 [df / c], d is the distance between the two nodes, c is the speed of light, and the brackets are rounding functions. The maximum frequency fmax = Mc / 4L, F is the fidelity that the communication process needs to meet, and Pg (F) is the probability of successfully meeting the fidelity, expressed as:

[0080]

[0081] Where η = e -ζd is the attenuation factor, ζ is the attenuation rate, and the quantum channel establishment rate of the basic link is mainly related to the fidelity and the length of the basic link. When the communication distance d is 780km, the communication light wavelength is 850nm.

[0082] Step S103: using the multi-attribute quantum satellite switching strategy of the quantum genetic algorithm according to the fitness function, integrating the service parameters provided by multiple quantum satellites, and selecting the quantum satellite with the best comprehensive switching performance.

[0083] Specifically: Based on the traditional genetic algorithm, the quantum genetic algorithm is used for optimization. The traditional genetic algorithm is prone to excessive iterations due to selection, crossover and mutation, slow convergence rate, and is more likely to fall into local extreme values. The quantum genetic algorithm introduces the quantum state vector expression into the gene code and uses quantum logic gates to evolve chromosomes, achieving better results than the traditional genetic algorithm.

[0084] The flow chart of the multi-attribute quantum satellite switching strategy based on quantum genetic algorithm is as follows: Figure 5 In order to improve user experience and resource utilization of the system, the various service parameters provided by multiple quantum satellites are integrated to select the quantum satellite with the best comprehensive performance. The algorithm steps are as follows:

[0085] S3001: The user initiates a service request, initializes the population Q(t0), and randomly generates n chromosomes encoded with quantum bits, that is, the accessible satellite set S = {S1, S2, S3, ... Sn};

[0086] S3002: According to the service request sent by the user, obtain the service type attribute value data and the access scheme related parameter data, perform a measurement calculation on each individual in the initial population Q(t0) according to the fitness function, and obtain the corresponding definite solution P(t0);

[0087] S3003: Perform fitness evaluation on each determined solution;

[0088] S3004: If there is only one quantum satellite in the current set S, then the quantum satellite can be directly accessed. When the current set S contains multiple quantum satellites, the weight coefficient of each satellite is calculated according to steps S2002 and S2003 and substituted to obtain the network fitness value of accessing the current satellite;

[0089] S3005: Record the best individual and the corresponding fitness;

[0090] S3006: Determine whether there is an optimal satellite, and exit if the end condition is met, otherwise continue calculation;

[0091] S3007: In the population Q(t), each individual is measured to obtain a corresponding definite solution;

[0092] S3008: Evaluate the fitness of each determined solution;

[0093] S3009: Use the quantum rotating door U(t) to change the individuals and obtain a new population Q(t+1);

[0094] S3010: Record the best individual and the corresponding fitness;

[0095] S3011: Increase the number of iterations t by 1, and return to step S3007 to continue calculation.

[0096] Step S104: verifying through simulation experiments that the multi-attribute quantum satellite switching strategy using the quantum genetic algorithm according to the fitness function reduces the switching failure rate and reduces the blocking rate of new calls.

[0097] In order to further verify the effect of reducing the switching failure rate and the blocking rate of new calls by using the multi-attribute quantum satellite switching strategy proposed in the present disclosure based on the fitness function and the quantum genetic algorithm, the following simulation experiments were conducted:

[0098] To verify and compare the optimization speed of quantum genetic algorithm (QGA) and classical genetic algorithm (GA), the evolutionary generations of the two algorithms were set to 100 and the population number was set to 40, and a comparative test was conducted on the optimization models of the two algorithms in the MATLAB environment. Figure 6 As shown in the figure, with the increase of evolutionary generations, the optimal fitness value of each generation of quantum genetic algorithm and classical genetic algorithm also increases. From the simulation results, it can be seen that the convergence speed of quantum genetic algorithm is faster than that of classical genetic algorithm, making the algorithm more adaptable and efficient, while the classical genetic algorithm is prone to fall into the phenomenon of local extreme value.

[0099] The performance of the proposed comprehensive weighted access selection algorithm based on fitness function, namely the comprehensive weighted access selection algorithm with bit error rate, delay and channel establishment rate constraints, and the minimum bit error rate priority access (Q-min), minimum delay priority access (T-min) and maximum channel establishment rate priority access (V-max) selection algorithms are evaluated. By comparing the simulation result graphs, the performance in terms of call blocking rate and switching failure rate is compared and analyzed.

[0100] In the entire network, the call blocking rate is defined as the ratio of the number of failed incoming calls to the total number of calls. The new call blocking rate is one of the key parameters for judging the performance of a switching selection algorithm. Figure 7 As shown in the figure, under different algorithms with different reference parameters, when the session arrival rate changes, the dynamic change of the call blocking rate. Under each algorithm, the increase of the session arrival rate will lead to a larger and larger network load, and the call blocking rate will continue to rise until it reaches a stable level. Compared with the other three algorithms, the access selection algorithm based on fitness function has a lower new call blocking rate.

[0101] In addition, at some point in the future, if a user is within the coverage of multiple quantum satellites and must switch to other satellites during the access process in order to work normally, the switching failure rate can be used as an indicator to evaluate the user access performance in this case.

[0102] The handover failure rate is defined as the ratio of the number of handover failures to the total number of handovers, such as Figure 8 As shown in the figure, the switching failure rates under some different algorithms are given. When the number of user service requests increases, the switching failure rate of the satellite network gradually increases for each access selection algorithm. The change in the slope of each curve represents the performance of each. It can be seen from the curve that the switching failure rate of the comprehensive weighted switching algorithm based on the fitness function is low. The reason why the switching success rate of the other three algorithms is not high is that the minimum bit error rate, minimum delay priority and maximum channel establishment rate priority access selection algorithms only focus on their own parameters and do not comprehensively consider the quality of the global network system. The access selection algorithm with a multi-objective function integrates the three parameters together and comprehensively considers more factors, so it can provide better service quality for ground station users and enhance the switching success rate of the satellite network.

[0103] The results show that the multi-attribute quantum satellite switching strategy based on quantum genetic algorithm has the ability to achieve better load balancing while reducing call blocking rate and switching failure rate, thus verifying the effectiveness of the proposed method. For example, when the session arrival rate is 5 sessions / s, the call blocking rate based on fitness function comprehensive weighted switching is reduced by 3.92%, 3.83%, and 3.8% respectively compared with the switching strategy based on minimum bit error rate, minimum transmission delay, and maximum channel establishment rate.

[0104] It should be noted that although several units of the system for action execution are mentioned in the above detailed description, this division is not mandatory. In fact, according to the embodiment of the present disclosure, the features and functions of two or more units described above can be concretized in one unit. Conversely, the features and functions of a unit described above can be further divided into multiple units for concretization. Some or all of the units can be selected according to actual needs to achieve the purpose of the disclosed solution. Those of ordinary skill in the art can understand and implement it without paying creative work.

[0105] Those skilled in the art will readily appreciate other embodiments of the present disclosure after considering the specification and practicing the invention disclosed herein. This application is intended to cover any modification, use or adaptation of the present disclosure, which follows the general principles of the present disclosure and includes common knowledge or customary techniques in the art that are not disclosed in the present disclosure. The specification and examples are intended to be exemplary only, and the true scope and spirit of the present disclosure are indicated by the appended claims.

Claims

1. A multi-attribute quantum satellite switching strategy based on quantum genetic algorithm, characterized in that: The following steps are involved: Establish a communication system model for quantum satellites; According to the communication system model of quantum satellite, based on the three properties of channel bit error rate, transmission delay and channel establishment rate between particles of quantum satellite, a fitness function is established by comprehensive weighting; According to the fitness function, a quantum satellite switching strategy with multiple attributes of a quantum genetic algorithm is used to select a quantum satellite with the best switching comprehensive performance; The simulation experiment verifies that the multi-attribute quantum satellite switching strategy using the quantum genetic algorithm according to the fitness function reduces the switching failure rate and the blocking rate of new calls.

2. According to claim 1, the multi-attribute quantum satellite switching strategy based on quantum genetic algorithm is characterized in that: The communication system model of the quantum satellite is an Iridium mobile satellite communication system model.

3. According to claim 1, the multi-attribute quantum satellite switching strategy based on quantum genetic algorithm is characterized in that: The expression of the fitness function is: f(x)=αQ+βK+γV (1) Among them, Q represents the inverse of the channel bit error rate, K represents the inverse of the transmission delay, V represents the channel establishment rate, α is the weighting coefficient of the quantum bit error rate, β is the weighting coefficient of the transmission delay, γ is the weighting coefficient of the channel establishment rate, and α+β+γ=1 is satisfied.

4. According to claim 1, the multi-attribute quantum satellite switching strategy based on quantum genetic algorithm is characterized in that: The expression of the channel bit error rate is: Where W(λ) is the background radiation spectrum, θ r is the receiver field of view, τ is the time window, n is the number of detectors, μ is the average number of photons per pulse, T cha is the transmission rate of the quantum channel, P acq is the single photon capture probability, T app is the transmission rate of the system device, η det is the quantum efficiency of the single-photon detector, F mea is the measurement factor.

5. According to claim 1, the multi-attribute quantum satellite switching strategy based on quantum genetic algorithm is characterized in that: The expression of the transmission delay is: Where T' is the average time of Bell basis measurement between nodes, T" is the wireless transmission delay between nodes, and m is the number of nodes in the intermediate satellite transmission.

6. The multi-attribute quantum satellite switching strategy based on quantum genetic algorithm according to claim 1 is characterized in that: The expression of the channel establishment rate is: V(F)=f max ·P g (F) (4) Among them, V represents the channel establishment rate, F is the fidelity that the communication process needs to meet, and P g (F) is the probability of successfully satisfying F, the maximum frequency f max =MC / 4d, M is the storage space value of entangled photons, M=4[df / c], f is the operating frequency of the entangled photon pair, d is the distance between the two nodes, C is the speed of light, and the square brackets are rounding functions.

7. The multi-attribute quantum satellite switching strategy based on quantum genetic algorithm according to claim 6 is characterized in that: The expression for the probability of successfully satisfying F is: Where η = e -ζd is the attenuation factor and ζ is the attenuation rate.

8. The multi-attribute quantum satellite switching strategy based on quantum genetic algorithm according to claim 1 is characterized in that: The algorithm steps of the multi-attribute quantum satellite switching strategy using the quantum genetic algorithm according to the fitness function are: According to the service request, the parameters of the three attributes of the channel bit error rate, transmission delay and channel establishment rate between particles of each quantum satellite are obtained, and the fitness function is applied to each individual in the initial population Q(t0) to measure and calculate, and the corresponding definite solution P(t0) is obtained; Perform fitness evaluation on each of the determined solutions P(t0), and record the optimal individual and the corresponding fitness; According to the fitness evaluation results, it is determined whether there is an optimal quantum satellite for switching. If there is an optimal quantum satellite for switching, the switching is completed. If there is no optimal quantum satellite for switching, a new population Q(t) is generated and the calculation continues. In the population Q(t), each individual in the population is measured and calculated according to the fitness function to obtain the corresponding definite solution P(t), and the fitness of each definite solution P(t) is evaluated; Use the quantum rotating door U(t) to change the individuals and obtain a new population Q(t+1); Record the best individual and the corresponding fitness; According to the fitness evaluation results, it is judged whether there is an optimal quantum satellite for switching. If there is an optimal quantum satellite for switching, the switching is completed. If there is no optimal quantum satellite for switching, the number of iterations t is increased by 1 and the calculation is continued.

Images