Low earth orbit satellite network switching method and system based on multi-attribute decision

Abstract

The invention discloses a low-orbit satellite network switching method and system based on multi-attribute decision, and belongs to the field of satellite network mobility management, and the method comprises the steps: predicting the call duration of each user, obtaining a satellite coverage time evolution graph, building a function of the elevation angle of a user ui relative to each satellite covering the user ui along with the time, and carrying out the switching of the user ui; a user elevation angle function theta i, j (tau) is obtained; when the user ui newly accesses the low earth orbit satellite network or the service satellite of the user ui changes, the switching time of next inter-satellite switching of the user ui is predicted; when the switching time of the user ui arrives, constructing a multi-objective function # imgabs0 # for the user ui, wherein the multi-objective function # imgabs1 # comprises the service capacity Ci, j (t) of the satellite sj to the user ui, the average elevation angle Ei, j (t) of the user ui to the satellite sj and the number Lj, t of residual channels of the satellite sj; and solving a satellite which maximizes the multi-objective function # imgabs2 # as a target satellite switched by the user ui this time. According to the invention, the QoE of the user in the service period of the low-orbit satellite network can be improved.

Description

Technical Field

[0001] The present invention belongs to the field of satellite network mobility management, and more specifically, relates to a low-orbit satellite network switching method and system based on multi-attribute decision making. Background Art

[0002] With the rapid growth of mobile terminals and applications, wireless networks need to meet the ubiquitous connectivity needs in remote, rural and urban areas. However, due to the limited coverage of ground wireless networks, large-scale deployment of base stations is not a feasible way to meet this demand, especially in rural and marine areas. Satellite communications are an effective way to solve the above problems due to their wide coverage and high throughput. Compared with medium and high orbit satellites, low-orbit satellites usually operate within a range of 500-2000 kilometers and have the advantages of low construction and launch costs, low power consumption, light weight, and short propagation delay. Therefore, low-orbit satellite networks have been widely accepted as an effective way to achieve seamless global communications and will play an important role in the future sixth-generation mobile communication systems.

[0003] Although low-Earth orbit satellite networks can provide better global coverage and communication quality, they still face some challenges, one of the most important of which is frequent switching. Unlike ground networks with pre-deployed fixed base stations, low-Earth orbit satellites move very quickly. For example, in the Iridium system, the satellite can move at a speed of up to 7km / s. Therefore, the connection between users and satellites is highly dynamic and must be switched frequently during the duration of user services. An effective switching solution needs to be designed to ensure the user's service experience.

[0004] The existing low-orbit satellite switching scheme simply sets the switching time as the end of satellite coverage, ignoring the degradation of the satellite-to-ground link quality at the edge of the satellite coverage area, resulting in the user service experience (Quality of Experience, QoE) not being guaranteed for a period of time before switching to the service satellite. In addition, the existing low-orbit satellite switching schemes are mainly divided into two categories: single-attribute switching schemes and multi-attribute switching schemes. Three attributes are widely used in low-orbit satellite switching: remaining service time, instantaneous link quality, and number of available channels. No matter which one, it is impossible to consider the changes in the overall satellite-to-ground link quality during the candidate satellite coverage period, and it is impossible to guarantee the maximization of user QoE. Summary of the invention

[0005] In view of the defects of the prior art and the need for improvement, the present invention provides a low-orbit satellite network switching method and system based on multi-attribute decision-making, which aims to effectively solve the problem that the existing low-orbit satellite switching method ignores the overall link quality between the satellite and the ground, and improve the QoE of users during the low-orbit satellite network service period.

[0006] To achieve the above object, according to one aspect of the present invention, a low-orbit satellite network switching method based on multi-attribute decision making is provided, comprising:

[0007] For each user u accessing the low-orbit satellite network i , predict its call duration, and obtain the time at user u based on the satellite ephemeris data i The position of each satellite during the call duration and the satellite's i The coverage situation of the satellite can be obtained by looking at the satellite coverage time evolution diagram;

[0008] According to the satellite coverage time evolution diagram, establish user u i Relative to the coverage user u i The elevation angle function of each satellite changes with time, and the user elevation angle function θ is obtained i,j (τ); τ represents satellite s j First coverage of user u i The time that has passed since

[0009] In user u i New access to low-orbit satellite network or user u i When the service satellite of user u changes, predict i The switching time of the next intersatellite switching;

[0010] In user u i When the switching time arrives, user u i Constructing multi-objective functions Multi-objective function Including satellites j For user u i The service capacity C i,j (t), user u i For satellites j The average elevation angle E i,j (t) and satellite s j The number of remaining channels L j,t ; Solve the multi-objective function The maximized satellite, as user u i The target satellite for this switch.

[0011] Furthermore, the user elevation angle function θ i,j The expression of (τ) is:

[0012]

[0013] Among them, ω E represents the angular velocity of the earth's rotation, i represents the inclination of the satellite orbit, ω S represents the angular velocity of the satellite, γ minIt represents the minimum angle between the user's point U and the sub-satellite point trajectory, Re represents the radius of the earth, and R represents the orbital radius of the satellite; ψ0 represents the angle between the current sub-satellite point H and the point Q on the sub-satellite point trajectory that is closest to point U.

[0014] Furthermore, satellites j For user u i The service capacity C i,j The expression of (t) is:

[0015]

[0016] in, and Represents satellite s j For user u i The coverage start time and coverage end time of BW i,j Indicates satellites j For user u i The allocated bandwidth, σ represents the noise power spectral density, S(θ i,j (τ)) represents the expression of the user received signal strength changing with elevation angle.

[0017] Furthermore, user u i For satellites j The average elevation angle E i,j The expression of (t) is:

[0018] Further,

[0019]

[0020] Where N(·) represents the normalization function; w1, w2 and w3 represent the weights of the three switching attributes, which are satellite s j For user u i The service capacity C i,j (t), user u i For satellites j The average elevation angle E i,j (t) and satellite s j The number of remaining channels L j,t ; Represents user u i The switching time, express Cover user u at all times i A collection of satellites.

[0021] Furthermore, the setting methods of w1, w2 and w3 include:

[0022] Calculate the subjective weight of each switching attribute through the analytic hierarchy process k represents the switching attribute number, where k = 1, 2, 3;

[0023] Calculate the objective weights of each switching attribute by the CRITIC method

[0024] According to Calculate the weights of each switching attribute.

[0025] Furthermore, predict the handover time of the next inter-satellite handover for user u i including:

[0026] (S1) Obtain the current serving satellite of user u i For user u i the coverage end time If the call end time of user u i is not later than then end the prediction of the handover time of user u i and update the next handover time of user u i to Otherwise, go to (S2);

[0027] (S2) Obtain the satellite set covering user u at time i and initialize n = 1;

[0028] (S3) Obtain the satellite set cov covering user u at time i t′ , calculate the average elevation angle of each satellite in the satellite set cov with respect to user u t′ during the time period, denote the minimum average elevation angle as E1, and calculate i the average elevation angle E2 of the satellite for user u during the time period; t i ot represents the preset time slot length, and the coverage relationship between the satellite and the user remains unchanged within a single time slot; sl

[0029] (S4) If or E1 < E2, then go to (S5); otherwise, add 1 to the value of n and then go to (S3);

[0030] (S5) End the prediction of the handover time of user u i and update the next handover time of user u i to

[0031] According to another aspect of the present invention, a computer program product is provided, including a computer program; when the computer program is executed by a processor, the above-mentioned low-orbit satellite network switching method based on multi-attribute decision-making provided by the present invention is implemented.

[0032] According to another aspect of the present invention, a computer-readable storage medium is provided, comprising a stored computer program; when the computer program is executed by a processor, the device where the computer-readable storage medium is located is controlled to execute the above-mentioned low-orbit satellite network switching method based on multi-attribute decision-making provided by the present invention.

[0033] According to another aspect of the present invention, there is provided a low-orbit satellite network switching system based on multi-attribute decision making, comprising:

[0034] A computer-readable storage medium for storing a computer program;

[0035] And a processor, used to read the computer program stored in the computer-readable storage medium to implement the above-mentioned low-orbit satellite network switching method based on multi-attribute decision-making provided by the present invention.

[0036] In general, the above technical solutions conceived by the present invention can achieve the following beneficial effects:

[0037] (1) The present invention constructs a user elevation angle function θ of a user relative to each satellite covering the user. i,j (τ), and based on the elevation function, the service capacity of each satellite to the user and the average elevation angle of the user to each satellite are calculated. When the user switches, a multi-objective function including the service capacity, the average elevation angle and the number of remaining channels is established, and the service satellite after the user switches is determined by solving the multi-objective function. The established multi-objective function The three switching attributes of service capacity, average elevation angle and remaining number of channels are comprehensively considered. Among them, the service capacity comprehensively reflects the satellite link quality and the remaining service time, the average elevation angle reflects the overall link quality during the entire satellite coverage period, and the remaining number of channels reflects the load of the satellite. Comprehensive consideration of these three switching attributes can fully consider the overall service capacity and load of candidate satellites, that is, non-service satellites covering users, so that the service satellite selected when the user switches can maximize the user QoE.

[0038] (2) The user elevation angle function established by the present invention fully considers the footprint geometry of the satellite and the user, and accurately reflects the function of the user's elevation angle relative to the satellite changing with time, providing a basis for the subsequent accurate calculation of service capacity and average elevation angle.

[0039] (3) Multi-objective function established by the present invention According to the importance of each switching attribute, a corresponding weight is assigned to each switching attribute. In a further preferred scheme, the AHP-CRITIC combined weighting method is used to transform the multi-objective optimization into a single-objective optimization problem. Specifically, the subjective weight of each switching attribute is first calculated by the hierarchical analysis method, and then the objective weight of each switching attribute is calculated by the CRITIC method. Finally, the sum of the subjective weight and the objective weight of each switching attribute is used as the weight of the corresponding switching attribute. This can effectively improve the solution efficiency without affecting the solution accuracy of the multi-objective function.

[0040] (4) The present invention does not directly use the end time of the satellite coverage time as the time for the user's next switching, but rather deduces the satellite coverage relationship at each time and the user's average elevation angle relative to each candidate satellite with a preset time slot length from the end time of the satellite coverage time. When it is found that the coverage relationship changes or the minimum average elevation angle of the candidate satellite is lower than that of the current service satellite, the time when the corresponding situation occurs is determined as the user's next switching time. Compared with the traditional method of directly using the end time of the service satellite's coverage time as the user's switching time, the present invention can switch the user to other service satellites before the user is at the edge of the service satellite coverage area, and ensure that the user can obtain better service quality after switching to the service satellite, thereby avoiding the impact of the decline in satellite-to-ground link quality at the edge of the satellite coverage area on the user's service experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 A flow chart of a low-orbit satellite network switching method based on multi-attribute decision making provided by an embodiment of the present invention;

[0042] Figure 2 A satellite coverage time evolution diagram provided by an embodiment of the present invention;

[0043] Figure 3 A satellite-ground geometry diagram provided for an embodiment of the present invention;

[0044] Figure 4 Geometry of satellite and user footprints provided for embodiments of the present invention;

[0045] Figure 5 A simulation diagram of average switching times provided by an embodiment of the present invention;

[0046] Figure 6 A simulation diagram of average signal-to-noise ratio provided by an embodiment of the present invention;

[0047] Figure 7 A simulation diagram of average channel utilization provided by an embodiment of the present invention;

[0048] Figure 8 This is a simulation diagram of average user QoE provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0049] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention. In addition, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0050] In the present invention, the terms "first", "second", etc. (if any) in the present invention and the accompanying drawings are used to distinguish similar objects but not necessarily to describe a specific order or sequence.

[0051] In order to solve the technical problem that the existing low-orbit satellite network switching method ignores the change of the overall link quality between the satellite and the ground within the coverage period of the candidate satellite when deciding the service satellite for the user when switching occurs, resulting in the inability to ensure the maximum user QoE, the present invention provides a low-orbit satellite network switching method and system based on multi-attribute decision-making. The overall idea is to make full use of the knowability of user position, ephemeris data and constellation configuration, establish the user's elevation angle function relative to the satellite through a geometric method, and construct the user's average elevation angle and satellite service capacity switching attributes based on this, together with the remaining number of channels of the satellite, construct a multi-objective function that can effectively reflect the overall link quality within the coverage period of the candidate satellite, thereby maximizing the user's QoE.

[0052] The following are examples.

[0053] Embodiment 1:

[0054] A low-orbit satellite network switching method based on multi-attribute decision making, such as Figure 1 As shown, including:

[0055] For each user u accessing the low-orbit satellite network i , predict its call duration, and obtain the time at user u based on the satellite ephemeris data i The position of each satellite during the call duration and the satellite's i The coverage situation of the satellite can be obtained by looking at the satellite coverage time evolution diagram;

[0056] According to the satellite coverage time evolution diagram, establish user u i Relative to the coverage user u i The elevation angle function of each satellite changes with time, and the user elevation angle function θ is obtained i,j (τ); τ represents satellite s j First coverage of user u i The time that has passed since

[0057] In user ui New access to low-orbit satellite network or user u i When the service satellite of user u changes, predict i The switching time of the next intersatellite switching;

[0058] In user u i When the switching time arrives, it is user u i Constructing multi-objective functions Multi-objective function Including satellites j For user u i The service capacity C i,j (t), user u i For satellites j The average elevation angle E i,j (t) and satellite s j The number of remaining channels L j,t ; Solve the multi-objective function The maximized satellite, as user u i The target satellite for this switch.

[0059] In practical applications, the ground network control center can infer call information from the user's type or historical data and learn the user's call duration.

[0060] In the low-orbit satellite network, the user position, ephemeris data and constellation configuration are known. Ephemeris data, also known as ephemeris table, refers to a table of satellite orbit parameters, that is, the table data indicates the scheduled position of a certain star at a certain time interval, or the scheduled position of a certain artificial satellite at a certain time interval; the constellation configuration includes information such as satellite orbit inclination, orbit radius, minimum service elevation angle, etc. Based on this known information, the satellite coverage time evolution diagram and the user elevation angle function can be constructed.

[0061] The satellite coverage time evolution diagram records the satellite coverage of the user at each time during the duration of the user's call. Figure 2 The figure shows an example of a satellite coverage time evolution diagram. During the duration of a user call, at each moment, a satellite that can cover the user will provide service to the user. This satellite is called a service satellite, and the remaining satellites that can cover the user are called candidate satellites.

[0062] The elevation angle of the user relative to the satellite reflects the link quality of the satellite to the user, and the larger the elevation angle, the higher the link quality. In traditional switching schemes, the instantaneous elevation angle is only calculated when the switching occurs, and the target satellite for this switching is selected based on the calculation result of the instantaneous elevation angle. This decision-making method ignores the quality of the overall satellite-to-ground link during the entire satellite coverage period and cannot guarantee the maximization of user QoE. To address this problem, this embodiment proposes to calculate a function of the time-varying elevation angle of the user relative to each satellite covering the user, that is, the user elevation angle function. Specifically, for any satellite that can cover the user, the satellite-to-ground geometry map composed of user location information, constellation configuration information, and satellite ephemeris data is as follows: Figure 3 As shown. Assume that the earth is a sphere, the satellite orbit inclination is i, and the orbit radius is R = Re + h, where Re is the radius of the earth and h is the orbit height. The satellite is located at point S and the user is located at point U. θ(τ) is the expression of the user elevation angle over time, and the variable τ represents the time after the satellite first covers the user. Minimum service elevation angle θ min The coverage area of ​​each satellite in the constellation is limited. Within the coverage area, the user elevation angle satisfies θ(τ)≥θ min The angular velocity of the satellite in the Earth-centered fixed (ECEF) coordinate system is ω≈ω S -ω E cosi, where ω S is the angular velocity of the satellite, ω E is the angular velocity of the Earth's rotation. Kepler constant μ = 398,600 (km 3 / s 2 ).

[0063] Satellite and user footprint geometry Figure 4 As shown. H and Q are located on the sub-satellite point trajectory, where H is the current sub-satellite point and Q is the point on the sub-satellite point trajectory closest to user U. The spherical triangle HQU is a spherical right triangle. According to the spherical right triangle and the spherical cosine theorem, we can get cosγ(τ)=cosψ(τ)×cosγ min . We can further obtain the expression of γ(τ) with τ as the variable: γ(τ)=cos -1 (cosψ(τ)×cosγ min ). Since the derivative of ψ(τ) is the angular velocity of the satellite in the ECEF coordinate system, integrating ω gives |ψ(τ)| = ∫ωdτ. Substituting the angular velocity ω into the expression of γ(τ), we get ψ(τ) = -(ω S -ω E cosi)τ+ψ0. Figure 3 The OPS triangle in the figure shows the relationship between γ(τ) and the elevation angle θ(τ): Combined with γ(τ), we can get the user elevation angle function θ(τ):

[0064]

[0065] When τ=0, the user elevation angle is minimum, and the elevation angle function satisfies θ(τ)=θ min , from the expression of γ(τ) and the relationship between γ(τ) and the elevation angle θ(τ), ψ0 can be obtained as:

[0066]

[0067] Further obtain the WSG84 coordinates of point Q (λ S ,η S ,0), and the WSG84 coordinates of point U (λ T ,η T ,0). Among them, λ S and η S are the latitude and longitude of point Q, respectively, and λ T and η T are the latitude and longitude of point U respectively. According to the haversine formula and the coordinates of the two points, γ can be obtained min .

[0068] Based on the above derivation, for user u i , relative to the coverage user u i Satellites j The user elevation angle function θ i,j The expression of (τ) is:

[0069]

[0070] Among them, ω E represents the angular velocity of the earth's rotation, i represents the inclination of the satellite orbit, ω S represents the angular velocity of the satellite, ψ0 represents the angle between the satellite subsatellite point H and point Q, γ min It represents the minimum angle between user U and the sub-satellite point trajectory, Re represents the radius of the earth, and R represents the orbit radius of the satellite.

[0071] When the user switches, this embodiment constructs a multi-objective function with service capacity, average elevation angle and number of remaining satellite channels as switching attributes. By solving the multi-objective function, the most suitable service satellite can be decided for the user to maximize the user QoE. Specifically, the service capacity comprehensively reflects the satellite link quality and the remaining service time, the average elevation angle reflects the overall link quality during the entire satellite coverage period, and the number of remaining channels reflects the load of the satellite. By comprehensively considering these three switching attributes, the overall service capacity and load of the candidate satellites can be fully considered, so that the service satellite selected when the user switches can maximize the user QoE.

[0072] In this embodiment, according to the Shannon formula and the user elevation function, the satellite s can be predicted. j Service capacity C for user i i,j The expression of (t) is:

[0073]

[0074] in, and Represents satellite s j For user u i The coverage start time and coverage end time of BW i,j Indicates satellites j For user u i The allocated bandwidth, σ represents the noise power spectral density, S(θ i,j (τ)) represents the expression of the user received signal strength changing with elevation angle. Service capacity comprehensively reflects the satellite link quality and remaining service time.

[0075] According to the user elevation angle function and satellite coverage time, the user u can be calculated i For satellites j The average elevation angle E i,j The expression of (t) is: Different from the instantaneous elevation angle, the average elevation angle can reflect the link quality of the satellite during the entire coverage period.

[0076] After calculating the satellite's service capacity and the average elevation angle of the user relative to the satellite based on the user elevation angle function, the multi-objective function can be calculated. The expression is as follows:

[0077]

[0078] Where N(·) represents the normalization function; w1, w2 and w3 represent the weights of the three switching attributes, which are satellite s j For user u i The service capacity C i,j (t), user u i For satellites j The average elevation angle E i,j (t) and satellite s j The number of remaining channels L j,t ; Represents user u i The switching time, express Cover user u at all times i A collection of satellites.

[0079] As a preferred implementation, this embodiment assigns weights to each switching attribute by combining weighting methods, and transforms multi-objective optimization into a single-objective optimization problem. A data matrix X = (x ij ) p×q , x ij represents the j attribute of the ith satellite. Preferably, the three types of switching attributes are normalized. The normalization function N(x ij ) has different forms depending on whether the switching attribute is a positive attribute or a negative attribute. Satellite service capacity, average elevation angle, and number of remaining channels are all positive attributes, so x ij Linear normalization is the switching attribute value minus the minimum value of the switching attribute among all candidate satellites, and the result is divided by the difference between the maximum value and the minimum value of the switching attribute among all candidate satellites.

[0080] The settings for w1, w2, and w3 include:

[0081] First, the subjective weight of each switching attribute is calculated by the Analytic Hierarchy Process (AHP). k represents the switching attribute number, k = 1, 2, 3; specifically including: initializing the switching attribute matrix. Preferably, the switching attributes are compared in pairs according to the influence of the switching attributes, and the comparison result is expressed in the form of a square matrix as A = (a ij ) 3×3 . The element a in the matrix ij is the result of pairwise comparison of switching attributes. The main diagonal elements in the comparison matrix are 1, and a ji =1 / a ij . Service capacity comprehensively reflects the remaining service time and service capabilities of the satellite, affecting the number of handovers and user experience, so service capacity is the most important factor. The number of available channels ensures load balancing and prevents satellite overload, which is the second most important handover factor. The average elevation angle affects the link quality and is the third most important handover factor. According to the analysis, a 22 、a 31 、a 32 Set to 2, 3, 2. After obtaining the matrix A, find the corresponding maximum eigenvalue λ max The eigenvector V satisfies AV = λ max V. Normalize V to get the subjective weight

[0082] Then, the objective weight of each switching attribute is calculated by the Criteria Importance Through Intercrieria Correlation (CRITIC) method. The CRITIC method determines the objective weight based on the variability and conflict of the evaluation indicators. The variability of attribute j is in is the average of all candidate satellite attributes j, The conflict of attribute j is Among them, r ij is the correlation coefficient. Preferably, the Pearson correlation coefficient is used. The information content of the indicator C j The objective weight W is the product of variability and conflict. j Calculated as

[0083] Finally, follow Calculate the weight of each switching attribute.

[0084] In order to further avoid the impact of the degradation of the satellite-to-ground link quality at the edge of the satellite coverage area on the user QoE, as a preferred implementation method, in this embodiment, the user u i The switching time of the next intersatellite switching includes:

[0085] (S1) Get user u i Current Service Satellites For user u i End time of coverage If user u i The call ends no later than Then end the user u i The switching time prediction of user u i The next switching time of is updated to Otherwise, go to (S2);

[0086] (S2) Acquisition Cover user u at all times i Satellite collection And initialize n=1;

[0087] (S3) Acquisition Cover user u at all times i The satellite collection cov t′ ,calculate Satellite collection cov within the time period t′ The satellites in the i The minimum average elevation angle is recorded as E1, and the Satellites in time period For user u i The average elevation angle E2;t slot Indicates the preset time slot length. The satellite coverage relationship to the user remains unchanged within a single time slot.

[0088] (S4) If the coverage relationship changes, or E1 < E2, that is, the average elevation angle of the candidate satellite is lower than that of the current satellite, then go to (S5); otherwise, after adding 1 to the value of n, go to (S3);

[0089] (S5) End the prediction of the handover time of user u i and update the next handover time of user u i to

[0090] In this embodiment, starting from the end moment of the satellite coverage time, the coverage relationship of the satellite at each moment and the average elevation angle of the user relative to each candidate satellite are deduced forward with a preset time slot length. When it is found that the coverage relationship changes or the minimum average elevation angle of the candidate satellite is lower than that of the current serving satellite, the occurrence moment of the corresponding situation is determined as the next handover moment of the user. Compared with the traditional method of directly using the end moment of the coverage time of the serving satellite as the user's handover moment, it can switch the user to other serving satellites before the user is located at the edge of the coverage area of the serving satellite, and ensure that after the user switches the serving satellite, a better service quality can be obtained, thereby avoiding the impact of the degradation of the satellite-ground link quality at the edge of the satellite coverage area on the user service experience.

[0091] Generally speaking, this embodiment can make full use of the knowability of the user's location, ephemeris data, and constellation configuration. By using a geometric method to establish the elevation angle function of the user, constructing the user's average elevation angle and the satellite service capacity switching attribute, it can comprehensively consider the overall link quality within the satellite coverage period; in the established multi-objective function, the handover decision comprehensively considers multiple handover attributes such as the user's average elevation angle, satellite service capacity, and remaining channel quantity, effectively balancing the satellite-ground link quality, the number of user handovers, and load balancing, and maximizing the user QoE; based on the established user elevation angle function, combined with the satellite coverage time evolution diagram, the user handover time is predicted in real time, effectively avoiding the problem of the degradation of the satellite-ground link quality caused by the user's handover at the end moment of the coverage of the serving satellite, and further improving the user QoE.

[0092] Embodiment 2:

[0093] A computer program product includes a computer program; when the computer program is executed by a processor, it implements the low-earth orbit satellite network handover method based on multi-attribute decision-making provided in the above Embodiment 1.

[0094] Embodiment 3:

[0095] A computer-readable storage medium includes a stored computer program; when the computer program is executed by a processor, it controls the device where the computer-readable storage medium is located to execute the low-earth orbit satellite network handover method based on multi-attribute decision-making provided in the above Embodiment 1.

[0096] Embodiment 4:

[0097] A low-orbit satellite network switching system based on multi-attribute decision making, comprising:

[0098] A computer-readable storage medium for storing a computer program;

[0099] And a processor, used to read the computer program stored in the computer-readable storage medium to implement the low-orbit satellite network switching method based on multi-attribute decision-making provided in the above-mentioned embodiment 1.

[0100] The following is a further analysis and explanation of the beneficial effects that can be achieved by the present invention in combination with the simulation results compared with the prior art. Specifically, the Starlink Phase I constellation was constructed, with 1,584 satellites operating in an orbit with an altitude of 550 km and an inclination of 53°, with a minimum service elevation angle of 40°. The low-orbit satellite network consists of The satellites are composed of M satellites with indexes, serving N satellites with indexes within the service duration. The service duration is divided into T time steps, with index t=1,2,...,T and time slot length t slot .

[0101] Introducing a binary indicator If user u i By satellites j Provide service at time t, then The satellite transmission power is 16dBw, and the maximum antenna gain of the transmitting antenna is 30dBi. Users are evenly distributed in the range of 30-32 degrees north latitude and 88-90 degrees east longitude. The carrier frequency band is 20GHz, the user bandwidth is fixed at 2MHz, the number of channels per satellite is 100, and the user receiving power is 0dBi. The low-orbit satellite network serves users through wide beams and spot beams. The wide beam is a signaling beam, and the spot beam is always aimed at the user through beam tracking. Therefore, there is only inter-satellite switching, and interference between users can be ignored. The network control center is responsible for mobility management in the entire area. Switching performance evaluation parameters include the number of switching times, average channel utilization, average signal-to-noise ratio, and average user QoE. 。 The method of the present invention is compared with the existing maximum elevation angle, maximum service time, maximum number of channels, and traditional multi-attribute switching methods: the maximum elevation angle method always selects the satellite with the largest elevation angle as the service satellite; the maximum channel number and maximum service time methods use the end time of the service time of the current service satellite as the switching time, and select the candidate satellites with the largest number of channels and the longest service time as the target satellites for this switching; the traditional multi-attribute switching method switches when the service satellite coverage ends, considering three switching attributes: instantaneous signal strength, remaining number of channels and remaining service time.

[0102] The number of fixed users is 200, and the average number of switching times of each method varies with time as follows: Figure 5 As shown. Figure 5 The results show that the average number of user switching increases with time. The maximum elevation angle method always selects the satellite with the largest elevation angle as the service satellite, so the number of switching increases rapidly. The number of switching of the method of the present invention is close to the maximum service time strategy, which is better than the maximum elevation angle, the maximum number of channels and the traditional multi-attribute switching method.

[0103] The average signal-to-noise ratio of each strategy is Figure 6 As shown, according to Figure 6 The results show that the maximum elevation angle strategy has the highest average signal-to-noise ratio because it always selects the satellite with the largest elevation angle as the service satellite. The method of the present invention avoids low-elevation angle service at the end of the satellite coverage period by predicting the switching time. At the same time, the method selects the target satellite by service capacity and average elevation angle. The two new attributes can better reflect the service capabilities of the candidate satellite. The average signal-to-noise ratio of the method of the present invention is higher than that of the maximum number of channels, the maximum service time method and the traditional multi-attribute switching method.

[0104] The average channel utilization of each method is as follows: Figure 7 As shown, the channel utilization is calculated using the Jain formula. Figure 7 The results show that the method of the present invention takes the number of remaining channels as one of the attributes, which effectively ensures the load balancing of the satellite network. The average channel utilization rate of the method of the present invention is better than the maximum elevation angle, maximum service time and traditional multi-attribute switching methods.

[0105] The average user QoE of each method is as follows: Figure 8 As shown in the figure, the calculation method of user average QoE is: Among them, ho i represents the cumulative number of handovers of user i within the service duration T, L j,t is the number of available channels of satellite j at time t, ho is the downlink signal-to-noise ratio between satellite j and user i. min , L, SNR max Used as normalization, they represent the minimum number of switches, the maximum number of channels provided by the satellite, and the maximum signal-to-noise ratio. Figure 8 The results show that the average user QoE of the method of the present invention is higher than that of all the comparison methods under different user numbers.

[0106] It will be easily understood by those skilled in the art that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A low-orbit satellite network switching method based on multi-attribute decision making, characterized in that: include: For each user u accessing the low-orbit satellite network i , predict its call duration, and obtain the time at user u based on the satellite ephemeris data i The position of each satellite during the call duration and the satellite's i The coverage situation of the satellite can be obtained by looking at the satellite coverage time evolution diagram; Establish user u according to the satellite coverage time evolution diagram i Relative to the coverage user u i The elevation angle function of each satellite changes with time, and the user elevation angle function θ is obtained i,j (τ); τ represents satellite s j First coverage of user u i The time that has passed since In user u i New access to the low-orbit satellite network or user u i When the service satellite of user u changes, predict i The switching time of the next intersatellite switching; In user u i When the switching time arrives, it is user u i Constructing multi-objective functions The multi-objective function Including satellites j For user u i The service capacity C i,j (t), user u i For satellites j The average elevation angle E i,j (t) and satellite s j The number of remaining channels L j,t ; Solve the multi-objective function The maximized satellite, as user u i The target satellite for this switch.

2. The low-orbit satellite network switching method based on multi-attribute decision making as claimed in claim 1, characterized in that: User elevation angle function θ i,j The expression of (τ) is: Among them, ω E represents the angular velocity of the earth's rotation, i represents the inclination of the satellite orbit, ω S represents the angular velocity of the satellite, γ min It represents the minimum angle between the user's point U and the sub-satellite point trajectory, Re represents the radius of the earth, and R represents the orbital radius of the satellite; ψ0 represents the angle between the current sub-satellite point H and the point Q on the sub-satellite point trajectory that is closest to point U.

3. The low-orbit satellite network switching method based on multi-attribute decision making as claimed in claim 2, characterized in that: Satellites j For user u i The service capacity C i,j The expression of (t) is: in, and Represents satellite s j For user u i The coverage start time and coverage end time of BW i,j Indicates satellites j For user u i The allocated bandwidth, σ represents the noise power spectral density, S(θ i,j (τ)) represents the expression of the user received signal strength changing with elevation angle.

4. The low-orbit satellite network switching method based on multi-attribute decision making as claimed in claim 3, characterized in that: User i For satellites j The average elevation angle E i,j The expression of (t) is:

5. The low-orbit satellite network switching method based on multi-attribute decision making as claimed in claim 4, characterized in that: Where N(·) represents the normalization function; w1, w2 and w3 represent the weights of the three switching attributes, which are satellite s j For user u i The service capacity C i,j (t), user u i For satellites j The average elevation angle E i,j (t) and satellite s j The number of remaining channels L j,t ; Represents user u i The switching time, express Cover user u at all times i A collection of satellites.

6. The low-orbit satellite network switching method based on multi-attribute decision making as described in claim 5 is characterized in that: The settings for w1, w2, and w3 include: Calculate the subjective weight of each switching attribute through the analytic hierarchy process k represents the switching attribute number, k = 1, 2, 3; Calculate the objective weight of each switching attribute through the CRITIC method according to Calculate the weight of each switching attribute.

7. The low-orbit satellite network switching method based on multi-attribute decision making according to any one of claims 1 to 6, characterized in that: Predict user u i The switching time of the next intersatellite switching includes: (S1) Get user u i Current Service Satellites For user u i End time of coverage If user u i The call ends no later than Then end the user u i The switching time prediction of user u i The next switching time of is updated to Otherwise, go to (S2); (S2) Acquisition Cover user u at all times i Satellite collection And initialize n=1; (S3) Acquisition Cover user u at all times i The satellite collection cov t′ ,calculate Satellite collection cov within the time period t′ The satellites in the i The minimum average elevation angle is recorded as E1, and the Satellites in time period For user u i The average elevation angle E2;t sl ot represents the preset time slot length, and the coverage relationship of the satellite to the user remains unchanged within a single time slot; (S4) If or E1 < E2, then go to (S5); otherwise, increment the value of n by 1 and then go to (S3); (S5) End the process for user u i The switching time prediction of user u i The next switching time of is updated to 8. A computer program product, characterized in that It includes a computer program; when the computer program is executed by a processor, it implements the low-orbit satellite network switching method based on multi-attribute decision-making as described in any one of claims 1 to 7.

9. A computer-readable storage medium, characterized in that: It includes a stored computer program; when the computer program is executed by a processor, it controls the device where the computer-readable storage medium is located to execute the low-orbit satellite network switching method based on multi-attribute decision-making as described in any one of claims 1 to 7.

10. A low-orbit satellite network switching system based on multi-attribute decision making, characterized in that: include: A computer-readable storage medium for storing a computer program; And a processor, used to read the computer program stored in the computer-readable storage medium to implement the low-orbit satellite network switching method based on multi-attribute decision-making as described in any one of claims 1 to 7.

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