Satellite link power and computing power optimization method

Abstract

The application discloses a method for optimizing satellite link power and computing power, and belongs to the technical field of satellite communication switching, and comprises the following steps: generating a satellite association identifier, wherein the satellite association identifier is generated based on satellite communication system dimensions for classifying and data aggregating satellites, the satellite communication system dimensions are used for classifying satellites to form satellite system classification and subclasses, and the satellite association identifier is used for establishing an association between the classified satellites and a switching prediction method; and analyzing the satellite association identifier, wherein actual satellite link power is obtained based on the satellite association identifier, and the actual satellite link power comprises the sum of received satellite link power, power consumed during satellite communication switching and power loss caused by natural environment influence.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of satellite communication switching, and particularly relates to a method for optimizing satellite link power and computing power. BACKGROUND

[0002] The on-board computer of the system adopts a real-time multitask operating system and an embedded microcomputer, and can complete multiple tasks such as communication between multiple users and the satellite, system resource management, user position management and the like on a highly integrated hardware platform. The satellite communication resources are implemented in a demand-oriented manner, the utilization rate of the channel is improved, and more effective information can be transmitted in a limited communication time window. The user terminal device on the ground also adopts a real-time multitask operating system and an embedded microcomputer, so as to realize miniaturization of the user terminal device. At the same time, the system adopts such a design to realize reloading and updating of the communication protocol and the signaling structure. Compared with general computer applications, the embedded real-time application system is a real-time system with characteristics such as high processing speed, special configuration and solid and reliable structure, and the corresponding software system should have characteristics, higher requirements and real-time performance. Switching also belongs to the category of network control, and is an important technical content in a cellular mobile communication system. The purpose of switching is to ensure that the system can continuously provide channel connection during user communication. In a ground cellular system, switching occurs when a user in communication moves from the coverage range of one cell to the coverage range of another cell. In a satellite cellular system, the mobility of the satellite makes the switching problem more complex. SUMMARY

[0003] The purpose of the embodiment of the application is to provide a method for optimizing satellite link power and computing power, which can solve the technical problem that the mobility of the satellite makes the switching of the satellite cellular system more complex in the prior art.

[0004] In order to solve the above technical problem, the application is implemented as follows:

[0005] In a first aspect, the embodiment of the application provides a method for optimizing satellite link power and computing power, which comprises

[0006] S101: generating a satellite association identifier, the satellite association identifier being generated based on classification and data aggregation of satellites in a communication system dimension, the classification of satellites in the communication system dimension being used to form satellite system classification and subclasses, and the satellite association identifier being used to establish an association between the classified satellites and a switching prediction method;

[0007] S102: analyzing the satellite association identifier, obtaining actual satellite link power based on the satellite association identifier, the actual satellite link power comprising the sum of received satellite link power, power consumed during satellite communication switching and power loss caused by natural environment influence.

[0008] Further, the S101 specifically comprises:

[0009] The switching keywords or key words are extracted from the preset switching mode, and the data aggregation is performed in the satellite system classification and sub-classification, the keywords or key words are obtained through satellite log data, and the preset switching mode includes channel switching, inter-beam switching, inter-satellite switching, gateway switching and network switching.

[0010] Further, the data aggregation is calculated by a feature extraction model, and the feature extraction model is used to judge the effect of the data aggregation.

[0011] Further, the switching prediction method comprises obtaining a preset number of switching trigger values of the preset switching mode, and obtaining a historical average switching threshold value of each of the preset switching modes, and completing switching prediction according to the switching trigger value and the historical average switching threshold value.

[0012] Further, the satellite association identifier comprises obtaining a classification to which a current satellite belongs and a satellite communication switching method, and the satellite communication switching method is used to calculate power consumed when the satellite communication switches.

[0013] Further, the power consumed when the satellite communication switches is calculated by using a power quantification model, and the power quantification model is:

[0014]

[0015] Further, the power loss caused by the natural environment is the power loss caused by the natural environment from the transmitting end to the receiving end of the satellite, and the power loss caused by the natural environment is obtained based on a terahertz natural environment attenuation model.

[0016] Further, the weather conditions included in the terahertz attenuation model include rain communication, cloud and fog communication, snow communication and sand dust climate.

[0017] Further, the satellite communication system is a 6G satellite system.

[0018] In a second aspect, an embodiment of the present application provides a satellite link power and computing power optimization system, comprising:

[0019] A generating module is configured to generate a satellite association identifier, the satellite association identifier is generated based on classification and data aggregation of satellites in a communication system dimension, the classification of satellites in the communication system dimension is used to form a satellite system classification and sub-classification, and the satellite association identifier is used to associate the classified satellites with a switching prediction method.

[0020] The analysis module is used for analyzing the satellite-associated identifier, and obtaining actual satellite link power based on the satellite-associated identifier, wherein the actual satellite link power includes the sum of received satellite link power, power consumed during satellite communication switching, and power loss caused by natural environment.

[0021] In the embodiment of the present application, the satellite-associated identifier is generated by generating a satellite-associated identifier, which is generated based on communication system dimensions for classifying and data aggregating satellites. The satellite-associated identifier is used to establish an association between the classified satellites and the switching prediction method. The satellite-associated identifier is analyzed to obtain actual satellite link power based on the satellite-associated identifier, wherein the actual satellite link power includes the sum of received satellite link power, power consumed during satellite communication switching, and power loss caused by natural environment. BRIEF DESCRIPTION OF DRAWINGS

[0022] Figure 1 is a flowchart of a satellite link power combination algorithm optimization method provided by the embodiment of the present application;

[0023] Figure 2 is a satellite classification diagram provided by the embodiment of the present application;

[0024] Figure 3 is a beam switching diagram caused by satellite movement provided by the embodiment of the present application.

[0025] The implementation, functional features and advantages of the present application will be further described with reference to the embodiments and the accompanying drawings. DETAILED DESCRIPTION

[0026] In order to make the purpose, technical solutions and advantages of the present application more clear, the technical solutions in the embodiments of the present application will be described clearly and completely with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0027] The embodiment of the present application provides a satellite link power combination algorithm optimization method, which will be described in detail below with reference to the drawings, specific embodiments and application scenarios.

[0028] Referring to Figure 1 , a flowchart of a satellite link power combination algorithm optimization method provided by the embodiment of the present application is shown.

[0029] The satellite link power combination algorithm optimization method provided by the embodiment of the present application comprises:

[0030] S101: generating a satellite association identifier, the satellite association identifier is generated based on classification and data aggregation of the satellite based on the communication system dimension, the satellite is classified based on the communication system dimension to form satellite system classification and subclass, and the satellite association identifier is used to associate the classified satellite with the handover prediction method.

[0031] Further, the classification result of classifying the satellite based on the communication system dimension can refer to Figure 2 , for example, according to the satellite communication range, it can be divided into global satellite system, international satellite system, regional satellite system and domestic satellite system; according to whether it is active, it can be divided into active satellite communication system and passive satellite communication system; according to the difference of multiplexing mode, it can be divided into frequency division multiplexing satellite communication system, time division multiplexing satellite communication system, space division multiplexing satellite communication system, code division multiplexing satellite communication system and hybrid multiple access satellite communication system; according to the frequency range, it can be divided into terahertz satellite communication system, very high frequency satellite communication system, ultra high frequency satellite communication system, extremely high frequency satellite communication system and laser satellite communication system; according to the difference of service range, it can be divided into fixed service satellite communication system, mobile service satellite communication system, broadcast television satellite communication system, scientific experiment satellite communication system, and meteorological, navigation, teaching and military satellite communication system; according to the movement mode, it can be divided into synchronous satellite communication system and moving satellite communication system, further, the moving satellite communication system can be further classified into random motion satellite communication system and phase motion satellite communication system. Among them, the satellite can be classified according to the actual needs of those skilled in the art, and the embodiment of the present application does not limit this.

[0032] Further, the S101 specifically includes: extracting the switching key or keyword of the preset switching mode into the satellite system classification and subclass for data aggregation, the keyword or keyword is obtained through satellite log data, and the preset switching mode includes channel switching, inter-beam switching, inter-satellite switching, gateway switching and network switching.

[0033] Optionally, the preset switching mode includes channel switching, inter-beam switching, inter-satellite switching, gateway switching and network switching.

[0034] The change of radio wave propagation environment or the change of interference condition will make the current user's communication channel unusable, at this time, the system needs to switch the user to another available channel in the same beam. In addition, dynamic channel allocation will also start the intra-beam channel switching.

[0035] Figure 3This is a schematic diagram illustrating beam switching caused by satellite movement, provided in an embodiment of this application. In terrestrial cellular systems, user movement leads to inter-cell channel switching, which corresponds to beam switching in satellite cellular systems. For non-GEO (Geosynchronous orbit) satellite cellular systems, cell switching caused by user movement is almost negligible; satellite movement is the primary cause of most switching events. Figure 3 As shown, a user initially communicates in satellite beam 1. Although the user is not moving, because the satellite is moving, after a certain period of time, the beam covering the user will no longer be beam 1 but the subsequent beam 2. If the user's call has not ended, communication needs to be switched to beam 2. However, too frequent switching is not good for the system. Implementing switching requires a series of signaling operations, and frequent switching will increase the signaling load of the system. In addition, the probability of switching failure will also increase, and a switching failure will cause the user's call to be interrupted, a situation known as dropped call. Compared with blocking, users find dropped call more unacceptable, so reducing the dropped call rate should be given more importance in the system design process. With this in mind, many systems have adopted beam designs to reduce the switching frequency. One method is to fix the position of the beam on the ground. As the satellite moves, it calculates the position and controls the direction of the beam projected to the ground. When the satellite moves forward relative to the ground, the beam moves backward relative to the satellite. Fixing the position of the beam on the ground reduces the switching frequency. Satellite systems that use this method include ICO (Medium Earth Orbit) and Teledesic (Global System for Satellite Communications). Another approach is to design the beams as elongated strips instead of the conventional circular shape. For example, the Globalstar system's beam design uses elongated strips for each beam, with the direction of the stripe aligned with the satellite's movement. Switching does not occur unless the satellite moves out of the user's field of view.

[0036] Even without the issue of inter-satellite handover, satellite handover still exists. If a satellite serving a user leaves the user before the call ends, the call needs to be handed over to a subsequent satellite. Satellite handover issues primarily exist in LEO (Low Earth Orbit) satellite systems; MEO (Medium Earth Orbit) satellite systems generally do not require this consideration. For example, the average apparent time of a satellite in the ICO system is approximately 2 hours, while the average apparent time in the Iridium system is 9 minutes. Therefore, satellite handover almost never occurs in the ICO system, but it is highly likely to happen in the Iridium system.

[0037] Another switching problem is switching to a different gateway during a call. For example, a user is initially connected to gateway 1 via satellite A. Before the call is completed, satellite A leaves the field of view of gateway 1, and a following satellite has not yet entered the field of view of the user. Thus, the call cannot be switched to the following satellite. At this point, satellite A enters the field of view of gateway 2, and the user call is switched to gateway 2, or the call is dropped. Gateway switching involves more signaling interaction and requires changing the routing of the user call in the ground network. In general, it should be avoided by careful design.

[0038] To reduce the cost of a user call, many satellite cellular systems are designed to operate in a dual mode, supporting both a ground mobile network and a satellite mobile network. If the ground mobile network is available, the ground mobile network is used preferentially. If a user call is established in the satellite mobile network, but the ground mobile network is found to be available during the call, the call needs to be switched to the ground mobile network. Conversely, if a user call is established in the ground mobile network, but the user moves out of the service area of the ground mobile network during the call, the call needs to be switched to the satellite mobile network.

[0039] Further, a keyword or a key word of the switching mode is obtained through satellite log data, and the obtained keyword or key word is brought into satellite system classification and sub-classification to aggregate data to form a satellite association identifier.

[0040] Further, S101 specifically further includes that the data aggregation is calculated by a feature extraction model, and the feature extraction model is used to judge the effect of the data aggregation.

[0041] Further, the feature extraction model can include a Root-Mean-Square Standard Deviation (RMSSTD) method for calculation. RMSSTD is used to calculate the comprehensive standard deviation of all variables in a group. The smaller the RMSSTD, the higher the similarity of individual objects within the group (within the cluster), and the better the aggregation effect. The calculation formula is as follows:

[0042]

[0043] Wherein, Si represents the sum of standard deviations of the i-th variable in each group, and p is the number of variables.

[0044] Further, the feature extraction model can use an R-square determination coefficient to calculate the effect of data aggregation. R-square represents the size of the difference between groups after aggregation, that is, the proportion of the variance of the original data that can be explained by the aggregation result. The larger the R-square, the higher the dissimilarity between groups (inter-cluster), and the better the aggregation effect. The R-square calculation formula is as follows:

[0045]

[0046] Wherein, W represents the difference degree of each group after aggregation grouping, B represents the difference degree between each group after aggregation grouping, T represents the total difference degree of all data objects after aggregation grouping, and T=W+B.

[0047] According to the idea of aggregation, a good aggregation result should be in the range of R-square E[0,11], and Sanare is closer to 1, which indicates the difference between each group, that is, B is larger, and the difference between each object in the same group (intra-cluster), that is, W is smaller, which is the effect that the aggregation analysis wants to achieve. The calculation formula is as follows:

[0048]

[0049] Wherein, p represents p indexes (variables), n represents n members, represents the overall average.

[0050] Further, the switching prediction method comprises obtaining a preset number of switching trigger values of the preset switching mode, and obtaining a historical average switching threshold value of each of the preset switching modes, and completing switching prediction according to the switching trigger value and the historical average switching threshold value.

[0051] Optionally, the switching prediction method can obtain the switching trigger values of the last 10 times of channel switching, inter-beam switching, inter-satellite switching, gateway switching, and network switching.

[0052] Optionally, the switching prediction method can obtain the switching trigger values of the last 18 times of channel switching, inter-beam switching, inter-satellite switching, gateway switching, and network switching.

[0053] Wherein, the skilled in the art can adjust the number of times of obtaining the switching trigger values of channel switching, inter-beam switching, inter-satellite switching, gateway switching, and network switching according to the actual situation, and the embodiments of the present application do not limit this.

[0054] Optionally, the handover prediction is performed according to the handover trigger value and the historical average handover threshold value, if the obtained handover trigger value exceeds the historical average handover threshold value, the handover success probability is predicted to increase by 10%, and if the obtained handover trigger value is lower than the historical average handover threshold value, the handover success probability is predicted to decrease by 10%.

[0055] S102: Analyze the satellite-associated identifier, and obtain an actual satellite link power based on the satellite-associated identifier, the actual satellite link power including a received satellite link power, a consumed power during satellite communication handover, and a power loss caused by natural environment.

[0056] Further, the satellite-associated identifier analysis includes obtaining a current satellite classification and a satellite communication handover method, and the satellite communication handover method is used to calculate the consumed power during satellite communication handover.

[0057] Further, the consumed power during satellite communication handover is calculated by using an algorithmic model, and the algorithmic model is as follows:

[0058]

[0059] In the formula, C br is the total algorithmic demand; f(x) is a mapping function; α i , β j , and γ k are mapping proportion coefficients; and q is redundant algorithmic power. Taking parallel computing capability as an example, assuming that there are b1, b2, and b3, three different types of parallel computing chip resources, f(b j ) represents a mapping function of the parallel computing capability provided by the jth parallel computing chip b, and q2 represents redundant algorithmic power of parallel computing.

[0060] Further, the power loss caused by the natural environment is a power loss caused by the natural environment from a satellite transmitting end to a satellite receiving end, and the power loss caused by the natural environment is obtained based on a terahertz natural environment attenuation model.

[0061] Optionally, the terahertz attenuation model includes weather conditions such as rain communication, cloud and fog communication, snowfall communication, and sand and dust climate. Different natural weather conditions will use different calculation formulas to calculate the radio wave signal attenuation procedure.

[0062] (1) Rain communication signal attenuation and attenuation threshold setting

[0063] When radio waves are transmitted in the line of sight, in addition to the attenuation in the air, they will also encounter rainwater attenuation; if they are propagated during rain. The attenuation rate y caused by rainfall is shown in formula (5).

[0064] γ R= KR A (5)

[0065] Wherein, R is rainfall, unit is mmh. K and A are parameters of polarization in horizontal and vertical two different cases. The specific algorithm is not discussed here.

[0066] According to formula (5) and taking different frequencies and rainfall, the relationship between the attenuation rate and the rainfall can be obtained by simulation. The attenuation rate will increase with the increase of the rainfall, and the increasing speed is relatively fast.

[0067] Further, the threshold setting unit of the rainwater communication signal is dB / km.

[0068] (2) Attenuation and attenuation threshold setting of cloud and fog communication signals

[0069] The cloud and fog attenuation rate can be calculated by an empirical formula, and the specific algorithm is shown in formula (6).

[0070]

[0071] In formula (6), f is the working frequency, unit is GHz: is the visibility.

[0072] The international regulation on visibility is: dense fog, V < 50m; thick fog, 50m < V < 200m; light fog, 200m < V < 500m. The selected range of visibility of the relationship between the attenuation rate and the frequency and the visibility is 20-500m.

[0073] Further, the analysis frequency of the atmospheric attenuation rate in the present application is 0-350GHz, and the specific value range can also be set according to the requirements of those skilled in the art, and the embodiments of the present application do not limit this.

[0074] Further, the threshold setting unit of the cloud and fog communication signal is dB / km and GHz 20-500m (visibility).

[0075] (3) Attenuation and attenuation threshold setting of snowfall communication signals

[0076] The radio wave attenuation rate y caused by snowfall can be approximately expressed by formula (7)

[0077] γ s = 7.47 x 10 -5 f x I (1 + 5.77 x 10 -5 f 3 I 0.6 ) (7)

[0078] In formula (7), f is the working frequency, unit: Gz; y is the snowfall intensity (mmh), unit: dm, which is the height of snow melting into water in a unit volume per hour. Among them, the frequency above 150 GHz is greatly affected by the snowfall intensity, and the frequency below 150 GHz is relatively less affected by the snowfall intensity.

[0079] Further, the snowfall communication signal threshold setting mode is that the frequency above 150 GHz is greatly affected by the snowfall intensity, and the alarm is recommended.

[0080] (4) Attenuation rate and attenuation threshold setting of sand weather characteristics

[0081] If the three weather conditions of floating dust, blowing sand and sandstorm often occur, the attenuation of the communication signal is more obvious; in the sandstorm weather, there are large sand particles and small dust particles, which have a greater influence on the propagation of millimeter waves and terahertz waves. Sand dust can be divided into natural formation and artificial formation. Among them, the artificially formed sand dust involves sand dust generated by explosion or vehicle travel. The shape of sand particles has complex diversity, and the shape of sand particles is also different in different regional environments and causes of sand dust. The distribution of sand particles is close to the logarithmic normal distribution, and the calculation method is shown in formula (8).

[0082]

[0083] In formula (8), N is the bulk density of sand dust (1 / m 3 ); D is the diameter of sand particles; p(D) is the density function of the size distribution of sand particles; m is the mean of lnD; a is the standard deviation of lnD.

[0084] The calculation method of the characteristic attenuation rate L is shown in formula (9).

[0085]

[0086] Among them, and are the real part and the imaginary part of the complex dielectric constant of wet sand dust, N is the bulk density of natural and artificial sand dust samples, the mean m and the standard deviation of lnD, and f is the frequency.

[0087] Table 1 shows the statistical parameters of the sand particle size distribution in the embodiments of the present application.

[0088] Table 1 Statistical parameters of sand particle size distribution

[0089] Type m N Explosive dust 8.489 0.663 6.272×10 Natural dust -9.718 0.405 1.630×10 Vehicle dust 9.448 0.481 1.880×10

[0090] The civil mobile communication system mainly faces the frequency loss caused by natural sand dust (such as sand dust, haze weather). In the embodiment of the application, natural sand dust parameters can be used for simulation. At 20 DEG C, the characteristic attenuation rate under different frequencies and water contents of sand dust weather is obtained from 0 to 350 GHz, and the water content is from 0 to 30%. Below the 20 GHz frequency band, the characteristic attenuation rate increases obviously with the increase of frequency, and above the 20 GHz frequency band, the characteristic attenuation rate increases relatively gently with the increase of frequency, and the change of the characteristic attenuation rate with the water content in the sand dust is not obvious. The more the water content, the smaller the attenuation. For a certain water content, the characteristic attenuation rate corresponding to the frequency from 0 to 350 GHz and the temperature from 0 DEG C to 60 DEG C, the characteristic attenuation rate only increases with the increase of frequency, and basically does not change with the temperature.

[0091] Further, the sand dust climate threshold setting mode is that below the 20 GHz frequency band, the characteristic attenuation rate increases obviously with the increase of frequency, and above the 20 GHz frequency band, the characteristic attenuation rate increases relatively gently with the increase of frequency.

[0092] Further, the satellite communication system in the embodiment of the application belongs to a 6G satellite communication system.

[0093] In the second aspect, the embodiment of the application provides a satellite link power and computing power optimization system, which comprises:

[0094] The generating module is configured to generate a satellite associated identifier, the satellite associated identifier is generated based on classification and data aggregation of satellites in the communication system dimension, the classification of satellites in the communication system dimension is used to form satellite system classification and subclasses, and the satellite associated identifier is used to associate the classified satellites with a switching prediction method.

[0095] The analysis module is configured to analyze the satellite associated identifier, obtain an actual satellite link power based on the satellite associated identifier, and the actual satellite link power comprises the sum of received satellite link power, power consumed during satellite communication switching, and power loss caused by natural environment.

[0096] Further, the satellite link power and computing power optimization system provided by the embodiment of the application further comprises:

[0097] The computing module is configured to extract a switching keyword or key word into the satellite system classification and subclasses for data aggregation in a preset switching mode, the keyword or key word is obtained through satellite log data, and the preset switching mode comprises channel switching, inter-beam switching, inter-satellite switching, gateway switching and network switching.

[0098] Further, the data aggregation is calculated by a feature extraction model, and the feature extraction model is used to judge the effect of the data aggregation.

[0099] Further, the switching prediction method comprises obtaining a preset number of switching trigger values of the preset switching mode, and obtaining a historical average switching threshold value of each of the preset switching modes, and completing switching prediction according to the switching trigger value and the historical average switching threshold value.

[0100] Further, the satellite correlation identifier is parsed, and a current satellite classification and a satellite communication switching method are obtained, and the satellite communication switching method is used to calculate power consumed during satellite communication switching.

[0101] Further, the power consumed during satellite communication switching is calculated by using a power calculation model, and the power calculation model is as follows:

[0102]

[0103] Further, the power loss caused by the natural environment is the power loss caused by the natural environment from the satellite transmitting end to the receiving end, and the power loss caused by the natural environment is obtained based on a terahertz natural environment attenuation model.

[0104] Further, the weather conditions included in the terahertz attenuation model are rain communication, cloud and fog communication, snow communication and sand dust climate.

[0105] Further, the satellite communication system is a 6G satellite communication system.

[0106] The above is only an embodiment of the present application and is not used to limit the present application. For those skilled in the art, the present application can have various changes and variations. Any modification, equivalent replacement, improvement, etc. within the spirit and principles of the present application shall be included in the scope of claims of the present application.

Claims

1. A method for satellite link power combining and computing power optimization, characterized in that, The method comprises: S101: generating a satellite association identifier, the satellite association identifier being generated based on satellite communication system dimension classification and data aggregation of satellites, the satellite communication system dimension classification being used to form satellite system classification and subclasses, and the satellite association identifier being used to associate the classified satellites with a switching prediction method; S102: analyzing the satellite association identifier, and obtaining actual satellite link power based on the satellite association identifier, the actual satellite link power comprising the sum of received satellite link power, power consumed during satellite communication switching, and power loss caused by natural environment; The S101 specifically comprises: extracting switching keywords or key words for a preset switching mode and inputting them into the satellite system classification and subclasses for data aggregation, the keywords or key words being obtained from satellite log data, and the preset switching mode comprising channel switching, inter-beam switching, inter-satellite switching, gateway switching, and network switching.

2. The method of claim 1, wherein, The data aggregation is calculated by a feature extraction model, and the feature extraction model is used to judge the effect of the data aggregation.

3. The method of claim 1, wherein, The switching prediction method comprises obtaining switching trigger values of a preset number of preset switching modes, and obtaining historical average switching threshold values of each preset switching mode, and completing switching prediction according to the switching trigger values and the historical average switching threshold values.

4. The method of claim 1, wherein, The analyzing of the satellite association identifier comprises obtaining the classification to which the current satellite belongs and a satellite communication switching method, and the satellite communication switching method is used to calculate the power consumed during satellite communication switching.

5. The method of claim 4, wherein, The power consumed during satellite communication switching is calculated by an algorithmic model, and the algorithmic model is: In the formula, is the total demand for computing power; f(x) is a mapping function of chip computing power; a represents a logic operation chip, b represents a parallel computing chip, and c represents a neural network acceleration chip; n is the total number of logic operation chips, m is the total number of parallel computing chips, and p is the total number of neural network acceleration chips; i, j, and k are chip serial numbers; α i , β j and γ k are mapping scale factors; q is redundant computing power, q1 (TOPS) represents logical operation redundant computing power, q2 (FLOPS) represents parallel computing redundant computing power, and q3 (FLOPS) represents neural network acceleration redundant computing power.

6. The method of claim 1, wherein, The power loss caused by the natural environment is the power loss caused by the natural environment from the transmitting end to the receiving end of the satellite, and the power loss caused by the natural environment is obtained based on a terahertz natural environment attenuation model.

7. The method of claim 6, wherein, The weather conditions included in the terahertz natural environment attenuation model are rain communication, cloud and fog communication, snow communication, and sand and dust climate.

8. The method of claim 1, wherein, The satellite communication system is a 6G satellite communication system. 9.A system for satellite link power combining and computing power optimization, characterized in that, The method comprises: a generating module, which is used to generate a satellite association identifier, the satellite association identifier being generated based on communication system dimension classification and data aggregation of satellites, the communication system dimension classification being used to form satellite system classification and subclasses, and the satellite association identifier being used to associate the classified satellites with a switching prediction method; specifically, switching keywords or key words are extracted for a preset switching mode and inputted into the satellite system classification and subclasses for data aggregation, the keywords or key words being obtained from satellite log data, and the preset switching mode comprising channel switching, inter-beam switching, inter-satellite switching, gateway switching, and network switching; an analyzing module, which is used to analyze the satellite association identifier, and obtain actual satellite link power based on the satellite association identifier, the actual satellite link power comprising the sum of received satellite link power, power consumed during satellite communication switching, and power loss caused by natural environment.

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