Method and device for configuring orbit parameters of low-orbit satellite network

Abstract

The embodiment of the invention provides a low-orbit satellite network orbit parameter configuration method and device. Due to orbit limitation of actual deployment of low-orbit satellites, low-orbit satellite base stations are randomly distributed on a spherical shell at a certain height from the ground according to an orbit, and the method comprises the following steps: constructing a distribution model of the low-orbit satellites according to actual orbit distribution characteristics; according to the air-ground channel characteristics, determining a channel model, and modeling satellite-user three-dimensional channel characteristics; quantizing useful and interference signal power distribution characteristics generated by a satellite base station, and further deducing a signal to interference plus noise ratio received at a user; setting of optimal low-orbit satellite base station deployment parameters is determined by giving an expression of the coverage rate under the model. According to the embodiment of the invention, the problem of how to configure low-orbit satellite deployment parameters actually depending on orbit distribution is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of low-orbit satellite communications, and in particular to a method for configuring deployment parameters of low-orbit satellite base stations under orbital constraints in the context of existing ground users supporting low-orbit satellite communications. Background Art

[0002] Low-orbit satellite communications have many advantages, such as wide-area coverage, low latency, and high bandwidth. They can provide stable communication services in remote areas, oceans, and air that are not covered by ground networks. Therefore, low-orbit satellite systems are regarded as an important part of 5G, 6G, and future networks.

[0003] However, due to the fact that the distribution characteristics of satellites are restricted by orbital distribution under actual deployment conditions, random point distribution cannot accurately simulate the distribution characteristics of low-orbit satellites. In addition, due to the particularity of the new arrival of space-ground, its channel characteristics also become complicated.

[0004] Therefore, how to configure the deployment parameters of low-orbit satellites under the constraints of orbital distribution, adjust the orbit and the number of satellites, select the appropriate deployment altitude, and achieve better performance is an urgent problem to be solved. Summary of the invention

[0005] The purpose of the present invention is to provide a method and device for configuring orbital parameters of a low-orbit satellite network, so as to analyze the performance of a low-orbit satellite communication system under orbital constraints and improve resource utilization. The specific technical solution is as follows:

[0006] Step 200, constructing a distribution model of low-orbit satellites according to actual orbit distribution characteristics.

[0007] Step 210, determining a channel model based on the space-to-ground channel characteristics, and modeling the three-dimensional channel characteristics between the satellite and the user.

[0008] Step 220, quantify the power distribution characteristics of the useful and interfering signals generated by the satellite base station, and then derive the signal-to-interference-noise ratio received at the user.

[0009] Step 230, by providing an expression for coverage under the model, determine the setting of optimal low-orbit satellite base station deployment parameters.

[0010] Optionally, constructing a distribution model of low-orbit satellites according to actual orbit distribution characteristics specifically includes:

[0011] It is necessary to first construct a distribution model of LEO satellite orbits, and then construct a distribution model of LEO satellites on orbit;

[0012] Given α n With β n For a track p n The angles between the z-axis and the x-axis. Then for this orbit, if αn OK, then no matter β n No matter how the orbit changes, the distance from any satellite base station to the ground user remains unchanged. Therefore, only α needs to be considered when modeling the orbit distribution. n Impact on distribution distance;

[0013] According to the geometric relationship, the cumulative distribution function of the shadow area of ​​the spherical shell can be expressed as:

[0014]

[0015] Among them, r is the radius of the spherical shell. In addition, the shadow area of ​​the spherical shell can be expressed as S cap =2πr 2 (1-cosα n ). Therefore, α n The cumulative distribution function of can be expressed as:

[0016]

[0017] Define the orbit of the service satellite as the service orbit p0, and its corresponding elevation angle α0 is α n Therefore, its cumulative distribution function can be expressed as

[0018]

[0019] Where N is the number of orbits. Finally, its probability density function can be expressed as:

[0020]

[0021] Since satellites are distributed on orbits, it is necessary to further construct a satellite constraint distribution model based on the orbit distribution model. m and For orbital p n The mth satellite on The angle between the track centerline and the z-axis. According to the relationship between the angles, For angle γ m The cumulative distribution function of can be expressed as:

[0022]

[0023] Therefore, the cumulative distribution function of γ0 can be expressed as:

[0024]

[0025] Where M is the number of satellites in one orbit. Finally, the probability density function of γ0 can be expressed as:

[0026]

[0027] Optionally, a channel model is determined according to the characteristics of the air-ground channel to model the three-dimensional channel characteristics of the satellite-user, specifically including:

[0028] When modeling the satellite-to-ground channel, large-scale asparagus and small-scale fading are used for simulation, where small-scale fading is simulated using shadow Rice distribution. The large-scale path loss to ground users can be expressed as:

[0029]

[0030] Among them, r e represents the radius of the earth. For small-scale fading that obeys the shadow Ricean distribution, the channel gain |h 2 The probability density function of is expressed as:

[0031]

[0032] Where Γ(·) is the gamma function, Represents shape and scale parameters.

[0033] Optionally, the power distribution characteristics of the useful and interfering signals generated by the satellite base station are quantified to derive the received signal-to-interference-to-noise ratio at the user, specifically including:

[0034] The useful signal power that serves the low-orbit satellite base station can be expressed as:

[0035]

[0036] According to different orbits, the interference power can be divided into the interference caused by satellites other than the service satellite in the service orbit and the cumulative sum of the interference caused by satellites in other orbits, expressed as:

[0037]

[0038] Therefore, the Laplace variation of interference power can be expressed as:

[0039]

[0040] Optionally, the step of determining the setting of optimal low-orbit satellite base station deployment parameters by providing an expression for coverage under the model specifically includes:

[0041] According to the definition of coverage, we can get:

[0042]

[0043] Based on this expression, we can get the impact of different deployment altitudes, number of orbits, and number of satellites on system performance, and thus get the optimal deployment parameters.

[0044] Optionally, the orbit-dependent satellite network parameter search device specifically includes: a determination module, a network side device and a terminal device.

[0045] Optionally, the determination module is used to determine channel environment parameters of the deployed area;

[0046] Network side equipment: includes a transceiver, a memory, a processor and a computer program stored in the memory and executable on the processor; when the processor executes the program, the step of confirming the optimal deployment parameters described in any one of claims 1 to 5 is implemented.

[0047] Beneficial Effects

[0048] From the above description, it can be seen that the present invention provides a method and device for configuring orbital parameters of a low-orbit satellite network. After quantifying the distribution characteristics of the deployed orbit, the satellite distribution under orbital constraints is modeled, and the deployed orbit and the number of satellites are adjusted according to different deployment altitudes, thereby reducing the impact of interference signals outside the service satellite and providing high-speed services for ground users. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 It is a system model diagram of a low-orbit satellite network orbit parameter configuration method and device of the present invention;

[0050] Figure 2 It is an implementation flow chart of the present invention;

[0051] Figure 3 It is a schematic diagram of the variation of ground user coverage with the number of deployed tracks;

[0052] Figure 4 It is a schematic diagram of the variation of ground user coverage with the number of satellites in orbit; DETAILED DESCRIPTION

[0053] In order to clarify the purpose, implementation scheme and technical advantages of the present invention, the present invention is further described in detail below in combination with specific embodiments and with reference to the accompanying drawings.

[0054] Figure 1 This is a practical application scenario of a method and device for configuring orbital parameters of a low-orbit satellite network of the present invention: low-orbit satellites serve ground users as service base stations, and satellite distribution is constrained by deployment orbits. The present invention aims to configure the deployment orbit and number of satellites of the low-orbit satellite network to maximize the performance of ground users.

[0055] Figure 2A schematic flow chart of a method and device for configuring orbital parameters of a low-orbit satellite network provided by the present invention includes:

[0056] Step 200, constructing a distribution model of low-orbit satellites according to actual orbit distribution characteristics.

[0057] It is necessary to first construct a distribution model of LEO satellite orbits, and then construct a distribution model of LEO satellites on orbit;

[0058] Given α n With β n For a track p n The angles between the z-axis and the x-axis. Then for this orbit, if α n OK, then no matter β n No matter how the orbit changes, the distance from any satellite base station to the ground user remains unchanged. Therefore, only α needs to be considered when modeling the orbit distribution. n Impact on distribution distance;

[0059] According to the geometric relationship, the cumulative distribution function of the shadow area of ​​the spherical shell can be expressed as:

[0060]

[0061] Among them, r is the radius of the spherical shell. In addition, the shadow area of ​​the spherical shell can be expressed as S cap =2πr 2 (1-cosα n ). Therefore, α n The cumulative distribution function of can be expressed as:

[0062]

[0063] Define the orbit of the service satellite as the service orbit p0, and its corresponding elevation angle α0 is α n Therefore, its cumulative distribution function can be expressed as

[0064]

[0065] Where N is the number of orbits. Finally, its probability density function can be expressed as:

[0066]

[0067] Since satellites are distributed on orbits, it is necessary to further construct a satellite constraint distribution model based on the orbit distribution model. m and For orbital p n The mth satellite on The angle between the track centerline and the z-axis. According to the relationship between the angles, For angle γ m The cumulative distribution function of can be expressed as:

[0068]

[0069] Therefore, the cumulative distribution function of γ0 can be expressed as:

[0070]

[0071] Where M is the number of satellites in one orbit. Finally, the probability density function of γ0 can be expressed as:

[0072]

[0073] Step 210, determining a channel model based on the space-to-ground channel characteristics, and modeling the three-dimensional channel characteristics between the satellite and the user.

[0074] When modeling the satellite-to-ground channel, large-scale asparagus and small-scale fading are used for simulation, where small-scale fading is simulated using shadow Rice distribution. The large-scale path loss to ground users can be expressed as:

[0075]

[0076] Among them, r e represents the radius of the earth. For small-scale fading that obeys the shadow Ricean distribution, the channel gain |h 2 The probability density function of is expressed as:

[0077]

[0078] Where Γ(·) is the gamma function, Represents shape and scale parameters.

[0079] Step 220, quantify the power distribution characteristics of the useful and interfering signals generated by the satellite base station, and then derive the signal-to-interference-noise ratio received at the user.

[0080] The useful signal power that serves the low-orbit satellite base station can be expressed as:

[0081]

[0082] According to different orbits, the interference power can be divided into the interference caused by satellites other than the service satellite in the service orbit and the cumulative sum of the interference caused by satellites in other orbits, expressed as:

[0083]

[0084] Therefore, the Laplace variation of interference power can be expressed as:

[0085]

[0086] Step 230, by providing an expression for coverage under the model, determine the setting of optimal low-orbit satellite base station deployment parameters.

[0087] According to the definition of coverage, we can get:

[0088]

[0089] Based on this expression, we can get the impact of different deployment altitudes, number of orbits, and number of satellites on system performance, and thus get the optimal deployment parameters.

[0090] Figure 3 It is the intention that the ground user coverage rate changes with the number of deployed orbits. The coverage rate represents the statistical probability that the user service link SIR meets the standard under a certain SIR threshold requirement. The horizontal axis represents the number of satellite deployment orbits. The simulation results show the impact of adjusting the satellite deployment altitude on the ground user performance under the number of orbital satellites. It can be seen that the optimal number of orbits changes under different satellite numbers and deployment altitudes. Therefore, in actual deployment, the number of orbits needs to be flexibly adjusted according to needs.

[0091] Figure 4 It is intended that the ground user coverage rate varies with the number of orbiting satellites. Figure 3 , the number of satellites in orbit also has an optimal value. When the number of satellites increases to a certain level, the performance of the system will not increase significantly if the number of satellites in orbit is further increased. Therefore, in order to avoid wasting resources, the number of satellites in orbit also needs to be dynamically adjusted as needed.

Claims

1. A method and device for configuring orbital parameters of a low-orbit satellite network, characterized in that: Including: Due to the orbital restrictions of the actual deployment of low-orbit satellites, low-orbit satellite base stations are randomly distributed according to orbits on a spherical shell at a certain height from the ground. According to the actual orbital distribution characteristics, a distribution model of low-orbit satellites is constructed; according to the characteristics of the air-ground channel, the channel model is determined to model the three-dimensional channel characteristics of the satellite-user; Quantify the power distribution characteristics of the useful and interfering signals generated by the satellite base station, and then derive the received signal-to-interference-to-noise ratio at the user; By giving an expression for coverage under this model, the setting of optimal low-orbit satellite base station deployment parameters is determined.

2. The method according to claim 1, characterized in that The construction of a distribution model of low-orbit satellites according to the actual orbit distribution characteristics specifically includes: It is necessary to first construct a distribution model of LEO satellite orbits, and then construct a distribution model of LEO satellites on orbit; Given α n With β n For a track p n The angles between the z-axis and the x-axis. Then for this orbit, if α n OK, then no matter β n No matter how the orbit changes, the distance from any satellite base station to the ground user remains unchanged. Therefore, only α needs to be considered when modeling the orbit distribution. n Impact on distribution distance; According to the geometric relationship, the cumulative distribution function of the shadow area of ​​the spherical shell can be expressed as: Among them, r is the radius of the spherical shell. In addition, the shadow area of ​​the spherical shell can be expressed as S cap =2πr 2 (1-cosα n ). Therefore, α n The cumulative distribution function of can be expressed as: Define the orbit of the service satellite as the service orbit p0, and its corresponding elevation angle α0 is α n Therefore, its cumulative distribution function can be expressed as Where N is the number of orbits. Finally, its probability density function can be expressed as: Since satellites are distributed on orbits, it is necessary to further construct a satellite constraint distribution model based on the orbit distribution model. m and For orbital p n The mth satellite on The angle between the track centerline and the z-axis. According to the relationship between the angles, For angle γ m The cumulative distribution function of can be expressed as: Therefore, the cumulative distribution function of γ0 can be expressed as: Where M is the number of satellites in one orbit. Finally, the probability density function of γ0 can be expressed as:

3. The method according to claim 1, characterized in that Determining the channel model according to the air-to-ground channel characteristics and modeling the three-dimensional channel characteristics of the satellite-user specifically includes: When modeling the satellite-to-ground channel, large-scale asparagus and small-scale fading are used for simulation, where small-scale fading is simulated using shadow Rice distribution. The large-scale path loss to ground users can be expressed as: Among them, r e represents the radius of the earth. For small-scale fading that obeys the shadow Ricean distribution, the channel gain |h| 2 The probability density function of is expressed as: Where Γ(·) is the gamma function, Represents shape and scale parameters.

4. The method according to claim 1, characterized in that: The quantified useful and interference signal power distribution characteristics generated by the satellite base station, and then deriving the received signal-to-interference-noise ratio at the user, specifically includes: The useful signal power that serves the low-orbit satellite base station can be expressed as: According to different orbits, the interference power can be divided into the interference caused by satellites other than the service satellite in the service orbit and the cumulative sum of the interference caused by satellites in other orbits, expressed as: Therefore, the Laplace variation of interference power can be expressed as:

5. The method according to claim 1, characterized in that The method of determining the setting of the optimal low-orbit satellite base station deployment parameters by providing an expression of the coverage rate under the model specifically includes: According to the definition of coverage, we can get: Based on this expression, we can get the impact of different deployment altitudes, number of orbits, and number of satellites on system performance, and thus get the optimal deployment parameters.

6. The method according to claim 1, characterized in that The method and device for configuring orbital parameters of a low-orbit satellite network specifically include: a determination module, a network side device, and a terminal device.

7. The method according to claim 6, characterized in that The determination module is used to determine the channel environment parameters of the deployed area; Network side equipment: includes a transceiver, a memory, a processor and a computer program stored in the memory and executable on the processor; when the processor executes the program, the step of confirming the optimal deployment parameters described in any one of claims 1 to 5 is implemented.

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