Universal capacity simulation system and method based on space-based short message spread spectrum measurement and control

Abstract

The invention discloses a universal capacity simulation system and method based on space-based short message spread spectrum measurement and control, belongs to the technical field of satellite communication, solves the problem that interference and conflicts among shared code channel users in a multiple access system affect user capacity calculation, and aims at performing simulation modeling on user satellites and dynamically simulating constellation configuration of low-orbit satellites. The service arrival time is simulated by establishing a service model, so that the design requirements of different low-orbit satellite systems are met; the transmitting power is dynamically adjusted based on the link budget, and the power difference of the user signal reaching the high-orbit satellite is balanced; the method comprises the following steps: performing simulation modeling on a high-orbit satellite based on antenna characteristics, and simulating all user channels by integrating various link conditions; according to the method, the interference and conflict conditions among the shared code channel users in the multiple access system are further quantitatively analyzed, the comprehensive influence of the multi-dimensional interference on the signal-to-noise ratio is quantified, and finally the user capacity corresponding to a certain sending success rate is obtained, so that the scientificity of decision making in system construction is improved, and the risk of system construction is reduced.

Description

Technical Field

[0001] This invention belongs to the field of satellite communication technology and relates to a general capacity simulation system and method based on space-based short message spread spectrum telemetry and control. Background Technology

[0002] In an asynchronous code division multiple access (CDMA) spread spectrum communication system for high-orbit satellites (geostationary orbit satellites, orbital altitude approximately 36,000 km), user capacity simulation calculations are performed when the served low-orbit satellites (orbital altitude not exceeding 2,000 km) use the same spreading codeword to transmit short messages for return space-based access. In CDMA systems, there is a certain correlation between time-overlapping user signals, leading to multiple access interference (MAI), which can limit user capacity when the number of users in the system is sufficiently large. Furthermore, due to limitations in the scale and cost of ground station equipment, the use of the same pseudo-random spreading codeword among multiple users may result in conflicts between user signals. When short messages overlap in time and the interference signal strength is sufficiently strong, the ground station receiver cannot distinguish user signals, causing signal acquisition failure, which is a major factor affecting user capacity.

[0003] Existing technologies, such as the invention patent with publication number CN118264307A, disclose a satellite communication interference cancellation method for high-capacity access. This method uses a method that searches for the minimum value of the Wienerhof equation quadratic surface to constrain the interference cancellation weights of multi-user signals, achieving rapid cancellation of multi-user interference while despreading, thus improving the efficiency of satellite communication interference cancellation. While this method reduces the impact of interference, its method of generating interference cancellation weights in real time and continuously adjusting cancellation coefficients is difficult to meet real-time requirements. When multiple users access concurrently, especially under conditions of severe signal overlap, the accuracy and effectiveness of interference cancellation are not as expected. Therefore, it is particularly important to propose a general capacity simulation system to quantitatively analyze the interference and conflict between users sharing a code channel in a multiple access system. Summary of the Invention

[0004] The technical solution of this invention is used to solve the problem of interference and conflict between users sharing a code channel in a multiple access system affecting user capacity calculation.

[0005] The present invention solves the above-mentioned technical problems through the following technical solutions:

[0006] A general capacity simulation system based on space-based short message spread spectrum telemetry and control includes:

[0007] The user distribution simulation module is used to simulate the number and location distribution of user satellites.

[0008] The short message service generation module is used to establish a service model and simulate the service arrival time for all users.

[0009] The transmit power control module is used to determine whether the user satellite has transmit power control capability and set the transmit power according to the user satellite engineering model;

[0010] The high-orbit satellite antenna simulation module is used to model the phased array antenna of a high-orbit satellite based on the antenna parameters and send the simulation calculation results to the star-ground channel simulation module.

[0011] The satellite-to-ground channel simulation module is used to simulate all user channels based on user locations and link conditions, and to calculate the received power of user satellite signals reaching the high-orbit satellite at different locations.

[0012] The multiple access interference and conflict determination module is used to select the target user location and simulate user capacity, and perform multiple access interference determination and conflict determination based on the arrival time of user satellite services.

[0013] The interference power calculation module is used to calculate the total multiple access interference power of the multiple access interference user to the target user according to the first influence condition, calculate the total conflict power of the conflicting user to the target user according to the second influence condition, and calculate the interference power of multiple access interference and conflict to the target user by superimposing them.

[0014] The user capacity statistics module is used to calculate the signal-to-noise ratio of the target user and to count the user capacity.

[0015] Furthermore, the user distribution simulation module specifically determines the number of users N and the orbital parameters of each user based on the construction requirements of the low-Earth orbit user constellation configuration.

[0016] The position and velocity of the user satellite are dynamically modeled in the simulation system. Based on the user satellite's mobility, the position of the user satellite changes with time as it moves along its orbit. The user position is denoted as in the spherical coordinate system. The center of the sphere is the origin; where r i θ represents the distance from the user satellite to the origin. i This represents the azimuth angle of the user satellite in the xy plane. This represents the angle between the user star and the z-axis, where i = 1, 2, ..., N.

[0017] Furthermore, the arrival time of the simulated service for all users in the short message service generation module is specifically as follows:

[0018] Within time T, the arrival time of each user satellite is t. n Let n = 1, 2, ..., N, and let t1 = 0. Then the arrival time t of the nth user is... n The calculation formula is:

[0019] t n =t n-1 +Δt

[0020] Where Δt represents the interval between the arrival times of services from two adjacent user satellites, t n-1 This represents the arrival time of the (n-1)th user.

[0021] Furthermore, since the arrival time of the service follows a Poisson distribution model, the interval between the arrival times of the two user satellite services follows an exponential distribution with parameter λ, where λ is a probability parameter representing the average number of events occurring per unit time. Therefore, Δt follows an exponential distribution with parameter λ. Using the inverse transformation sampling method, uniformly distributed random numbers are used to generate exponentially distributed random numbers, and Δt is represented by the following logic:

[0022] Δt=-log(1-rand) / λ

[0023] Where rand means to generate uniformly distributed random numbers in the range [0,1), and 1-rand means to restrict the range to the range [0,1).

[0024] Furthermore, the transmission power is set in the transmission power control module as follows:

[0025] If the user satellite has transmit power control capability, the transmit power is adjusted according to the link budget to balance the near-far effect; if the user satellite does not have transmit power control capability, the transmit power is fixed according to the actual power value; wherein, adjusting the user satellite transmit power value according to the link budget specifically means:

[0026] The following logic can be used to represent the signal power Pr received by a high-orbit satellite from the nth low-orbit satellite. n :

[0027] Pr n =Pt n ·Gt n ·Gr n ·L p ·L n

[0028] Among them, Pt n Let Gt be the launch power of the nth low-Earth orbit satellite. n For the transmit antenna gain of the nth low-Earth orbit satellite, Gr n For the gain of the high-orbit satellite receiving antenna, L p The path loss is expressed as λ′ is the signal wavelength, d n Let L be the distance from the nth low-Earth orbit satellite to the high-Earth orbit satellite. n Other losses.

[0029] Furthermore, the multiple access interference and conflict determination module performs multiple access interference determination and conflict determination specifically as follows:

[0030] When the timeline of the arrival time of other users' services overlaps with that of the target user, it is determined that other users are causing multi-address interference to the target user. The user IDs that are causing multi-address interference to the target user are recorded as the set of multi-address interference users.

[0031] When the arrival time of the target user's service falls within the conflict interval and overlaps with the timeline of the arrival time of other users' services, it is determined that other users have caused a conflict with the target user. The user IDs that caused the conflict with the target user are recorded, forming a set of conflicting users.

[0032] Furthermore, the first influencing condition in the interference power calculation module includes the overlap length, spreading code correlation, interference user location, and interference user transmission power; the second influencing condition includes the interference user location and interference user transmission power.

[0033] The total multiple access interference power P from the multiple access interference user to the target user is calculated using the following logic. MAI :

[0034]

[0035] Among them, Pr p Let p be the signal power received by the high-orbit satellite from the p-th low-orbit satellite, where p∈N. MAI N MAI For the set of multiple access interference users, ρ pj Let E[|ρ] be the normalized cross-correlation function of the spreading codes for user p and target user j. pj | 2 ] is |ρ pj | 2 Expected value;

[0036] There is no spreading gain during a collision; therefore, the total collision power is a direct sum of the powers of the colliding users. The total collision power P of the colliding users to the target user is calculated using the following logic. C :

[0037]

[0038] Among them, Pr q Let be the signal power received by the high-orbit satellite from the q-th low-orbit satellite, where q∈N. C N C For the set of conflicting users.

[0039] Further, the calculation of the signal-to-noise ratio (SNR) of the target user in the user capacity statistics module specifically involves: calculating the SNR of the target user when there is no interference, and the SNR of the target user when interference power is superimposed; wherein, the SNR of the target user j when interference power is superimposed is represented by the following logic:

[0040]

[0041] Among them, Pr j The high-orbit satellite receives the signal power of target user j, P noise P is the noise power. noise =N0·B, where N0 is the noise power spectral density, B is the baseband bandwidth after despreading, and P C P represents the total conflict power between conflicting users and the target user. MAI This represents the total multiple access interference power from multiple access interference users to the target user.

[0042] Furthermore, the user capacity statistics module specifically calculates user capacity as follows: A signal-to-noise ratio (SNR) decrease threshold ΔSNR is set. If SNR - SINR ≥ ΔSNR, the target user's short message transmission fails. The simulation is repeated M times, and the number of short message transmission failures (m) is counted to calculate the target user's short message transmission success rate. Obtain the system's short message transmission success rate under different user capacities.

[0043] This invention also provides a general capacity simulation method based on space-based short message spread spectrum telemetry and control, comprising the following steps:

[0044] S1 simulates the number and location distribution of user satellites;

[0045] S2, Establish a user star short message service model and simulate service arrival time for all user stars;

[0046] S3, based on the user satellite engineering model, determine whether the user satellite has the capability to control transmission power and set the transmission power;

[0047] S4, Model the phased array antenna of the high-orbit satellite based on the antenna parameters, and then execute S5;

[0048] S5. Based on the user's location and link conditions, simulate all user channels and calculate the received power of user satellite signals at different locations reaching the high-orbit satellite.

[0049] S6, Select the target user location, simulate user capacity, and determine multiple access interference and conflict based on service arrival time;

[0050] S7. Calculate the total multiple access interference power of the multiple access interference user to the target user according to the first influence condition, calculate the total conflict power of the conflicting user to the target user according to the second influence condition, and calculate the multiple access interference and conflict interference power to the target user by superimposing them.

[0051] S8 calculates the signal-to-noise ratio of the target user and counts the user capacity.

[0052] The advantages of this invention are:

[0053] This invention simulates and models user satellites based on user characteristics, dynamically simulating the constellation configuration of low-Earth orbit (LEO) satellites. It simulates service arrival times by establishing a service model to adapt to the design requirements of different LEO satellite systems. Based on link budget, it dynamically adjusts transmit power to balance the power differences in user signals arriving at high-Earth orbit (HEO) satellites, significantly reducing the suppression of weak signals by high-power users. Based on antenna characteristics, it simulates HEO satellites and simulates all user channels under various link conditions, reflecting the impact of the actual channel environment on signal reception power. Furthermore, it quantitatively analyzes interference and conflicts between users sharing code channels in multiple access systems, quantifying the comprehensive impact of multi-dimensional interference on the signal-to-noise ratio (SNR). Finally, it obtains the user capacity corresponding to a certain transmission success rate, evaluates the rationality of the system design, and thus improves the scientific nature of decision-making in system construction and reduces the risks of system construction.

[0054] This invention is applicable to the construction of complex systems such as high-Earth orbit (HEO) and low-Earth orbit (LEO) satellite constellations. It comprehensively considers various factors such as LEO satellite constellation configuration, number of LEO satellites, HEO satellite phased array antenna capabilities, and LEO satellite space-based short message access system. It statistically analyzes the interference and conflict between users in a shared code channel space-based short message spread spectrum access system, evaluates the short message access success rate in a realistic manner, and performs quantitative simulation calculations on the core key indicator of space-based short message user capacity to evaluate the rationality of the system design. The parameters in the simulation system can be dynamically configured according to the system design, and it has good application prospects. Attached Figure Description

[0055] Figure 1 This is a schematic diagram of a space-based short message spread spectrum telemetry and control scenario according to Embodiment 1 of the present invention;

[0056] Figure 2 This is a flowchart of a general capacity simulation method based on space-based short message spread spectrum measurement and control according to Embodiment 1 of the present invention;

[0057] Figure 3 This is a structural diagram of the general capacity simulation system based on space-based short message spread spectrum measurement and control according to Embodiment 1 of the present invention;

[0058] Figure 4 This is a schematic diagram of the shared code channel spread spectrum signal conflict interval in Embodiment 1 of the present invention;

[0059] Figure 5 This is a schematic diagram of multiple access interference and conflict determination in Embodiment 1 of the present invention;

[0060] Figure 6 This is a schematic diagram illustrating the relationship between user capacity and access success rate in Embodiment 1 of the present invention. Detailed Implementation

[0061] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below in conjunction with the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0062] The technical solution of the present invention will be further described below with reference to the accompanying drawings and specific embodiments:

[0063] Example 1

[0064] Figure 1 This is a schematic diagram of a space-based short message spread spectrum telemetry and control scenario in this embodiment. Low-Earth orbit spacecraft users send short message services to high-Earth orbit satellites using the same spread spectrum codewords. The high-Earth orbit satellites transparently forward the signals to ground stations for acquisition and demodulation. User capacity is statistically analyzed based on the general capacity simulation system provided by this invention.

[0065] like Figure 3 As shown, specifically, a general capacity simulation system based on space-based short message spread spectrum measurement and control is disclosed, including a user distribution simulation module, a short message service generation module, a transmission power control module, a star-ground channel simulation module, a multiple access interference and conflict determination module, an interference power calculation module, and a user capacity statistics module connected in sequence.

[0066] Furthermore, it also includes a high-orbit satellite antenna simulation module; the output terminal of the high-orbit satellite antenna simulation module is connected to the control terminal of the star-to-ground channel simulation module.

[0067] The user distribution simulation module is used to simulate the number and location distribution of user satellites. Specifically, it determines the number of users N and the orbital parameters of each user based on the construction requirements of the low-Earth orbit user constellation configuration. The simulation system dynamically models the positions and velocities of the user satellites, simulating their movement along their orbits over time, given their mobility. The user positions are denoted as follows in spherical coordinates: With the center of the sphere as the origin, where r i θ represents the distance from the user satellite to the origin. i This represents the azimuth angle of the user satellite in the xy plane. This represents the angle (elevation angle) between the user star and the z-axis, where i = 1, 2, ..., N.

[0068] Optionally, the constellation configuration is the Walker constellation, and the orbital parameters include the semi-major axis, eccentricity, orbital inclination, right ascension of the ascending node, argument of perigee, and true anomaly.

[0069] In this embodiment, a user satellite refers to a satellite that serves end users, is responsible for receiving and transmitting user data, or acts as an intermediary between ground stations and satellite networks to achieve signal transmission.

[0070] The short message service generation module is used to establish a service model and simulate the service arrival time for all user satellites. The accuracy of the service arrival time is determined based on the system spreading code rate, which serves as the basic basis for judging interference and collision between user satellites.

[0071] Optionally, the establishment of the business model specifically involves: modeling each user individually based on the actual business characteristics of the user star; or adopting a unified business model for all users.

[0072] The specific arrival time of the simulated satellite service for all users is as follows:

[0073] Within time T, the arrival time of each user satellite is t. n Let n = 1, 2, ..., N, and let t1 = 0. Then the arrival time t of the nth user is... n The calculation formula is:

[0074] t n =t n-1 +Δt

[0075] Where Δt represents the interval between the arrival times of services from two adjacent user satellites, t n-1 This represents the arrival time of the (n-1)th user.

[0076] In this embodiment, the Poisson distribution model is used as an example for illustration. Since the arrival time of services from two user satellites follows a Poisson distribution, the interval between their arrival times follows an exponential distribution with parameter λ, where λ is the probability parameter representing the average number of events occurring per unit time. Therefore, Δt follows an exponential distribution with parameter λ. In this embodiment, an inverse transformation sampling method can be used to generate an exponentially distributed random number from uniformly distributed random numbers. The following logic represents Δt:

[0077] Δt=-log(1-rand) / λ

[0078] Here, rand means to generate uniformly distributed random numbers in the range [0,1), and 1-rand means to restrict the range to the range [0,1) to avoid infinity when taking the logarithm.

[0079] The transmit power control module is used to determine whether the user satellite has transmit power control capability based on the user satellite engineering model, and to set the transmit power. If the user satellite has transmit power control capability, the transmit power is adjusted according to the link budget to balance the near-far effect, reduce the interference of high-power signals at the near end to low-power signals at the far end, and improve the overall user experience and system capacity. If the user satellite does not have transmit power control capability, the transmit power is fixed according to the actual power value.

[0080] This embodiment determines the functions and performance requirements of the user satellite based on the user satellite engineering model, and can determine whether the corresponding hardware equipment has power control function. It can be determined whether the user satellite has the transmission power control capability by querying the user satellite engineering model.

[0081] In this embodiment, when the user satellite has the capability to control its transmission power, the transmission power value of the user satellite is adjusted according to the link budget so that the transmission power value is consistent with the signal power between users when the satellite is in high orbit, thus avoiding the suppression of low-power signals by high-power signals and the generation of near-far effects; when the user satellite does not have the capability to control its transmission power, the transmission power value of the user satellite is set according to the actual situation.

[0082] The adjustment of the user satellite's transmit power based on the link budget specifically involves the following strategy when the user satellite has transmit power control capabilities: The transmit power can be adjusted according to the following strategy, using the following logic to represent the signal power Pr received by the high-orbit satellite from the nth low-orbit satellite. n :

[0083] Pr n =Pt n ·Gt n ·Gr n ·L p ·L n

[0084] Among them, Pt n The launch power of the nth low-Earth orbit satellite needs to be adjusted; Gt n Gr represents the transmit antenna gain of the nth low-Earth orbit satellite. n This refers to the gain of the high-orbit satellite receiving antenna. The gain is related to the position of the low-orbit satellite. Generally, the farther the low-orbit satellite is from the high-orbit satellite, the larger the beam scanning angle of the high-orbit satellite's phased array antenna, and the lower the receiving antenna gain. The specific gain value can be obtained in the high-orbit satellite antenna simulation module; L p The path loss is expressed as λ′ is the signal wavelength, d n L represents the distance from the nth low-Earth orbit satellite to the high-Earth orbit satellite. n Other losses, including atmospheric attenuation and pointing error, can be set based on engineering experience.

[0085] When a low-Earth orbit satellite reaches the location of a high-Earth orbit satellite, its transmission power reaches the level of the inter-user signal power Pr when the high-Earth orbit satellite is in orbit. n If all values ​​are Pr, then the transmit power Pt of each low-Earth orbit satellite can be calculated using the following logic. n :

[0086]

[0087] The high-orbit satellite antenna simulation module is used to model the high-orbit satellite phased array antenna according to the antenna parameters and send the simulation calculation results to the star-ground channel simulation module.

[0088] Specifically, the antenna parameters include antenna element type, operating frequency band, number of antenna elements, and antenna element spacing. The simulation calculation results include antenna performance such as antenna gain considering beam scanning loss. The simulation calculation results after modeling are used as design inputs and sent to the satellite-to-ground channel simulation module. In this embodiment, the antenna gain Gr received by high-orbit satellites under beam scanning loss is calculated using the following strategy. n :

[0089] For the two-dimensional planar phased array antennas commonly used in high-orbit satellites, their beam scanning reaches... Gain at time Using the following logical representation:

[0090]

[0091] in, N represents the elevation and azimuth angles of the beam pointing. x N represents the number of antenna elements in the x-direction. y G represents the number of antenna elements in the y-direction; element η is the gain of a single antenna element; η is the antenna array efficiency (including feed loss, impedance matching, etc., usually taken as 0.7 to 0.9); For two-dimensional array factors; cos a θ is the scanning loss, and a is an empirical exponent, which is affected by array mutual coupling, edge effects, etc., and is usually taken as 1 to 1.5. (Two-dimensional array factor) Using the following logical representation:

[0092]

[0093] Where k is the wave number, expressed as k = 2πλ′. d x and d y The unit spacing is defined as the x-axis and y-axis spacing.

[0094] The satellite-to-ground channel simulation module is used to simulate all user channels based on user location and link conditions, and to calculate the received power Pr of user satellite signals reaching the high-orbit satellite at different locations. n The link conditions include the operating frequency band f = cλ′ and the antenna gain considering scanning loss. Path loss L p Other losses L n wait.

[0095] In this embodiment, by simulating all user channels, the received power of user satellite signals at different locations reaching the high-orbit satellite is calculated, which serves as the basic basis for calculating interference power and collision power.

[0096] The multiple access interference and conflict determination module is used to select the target user location and simulate user capacity, and to determine multiple access interference and conflict based on the arrival time of user satellite services.

[0097] Specifically, the multiple access interference determination and conflict determination are as follows:

[0098] When the timeline of the arrival time of other users' services overlaps with that of the target user, it is determined that other users are causing multi-address interference to the target user. The user IDs that are causing multi-address interference to the target user are recorded as the set of multi-address interference users.

[0099] When the arrival time of the target user's service falls within the conflict interval and overlaps with the timeline of the arrival time of other users' services, it is determined that other users have caused a conflict with the target user. The user IDs that caused the conflict with the target user are recorded, forming a set of conflicting users.

[0100] In this embodiment, the target user location is first selected. Considering adverse conditions, this embodiment assumes that the target user is located at the edge of the coverage area of ​​the high-orbit satellite. At this time, the path loss and antenna scanning loss of the target user are relatively large. Therefore, the simulated user capacity is under poor conditions. When the target user is located in other locations, the user capacity will be improved.

[0101] Then, multiple access interference and collision determination is performed. Based on the arrival time of the user's satellite service, it is determined whether other users cause multiple access interference and collisions to the target user. On the one hand, multiple access interference will be generated between short message signals that overlap on the arrival time axis. The user numbers that cause multiple access interference to the target user are recorded, forming the multiple access interference user set N. MAI On the other hand, there is a possibility of signal collisions between short user messages sharing the code channel. Thanks to the delay capture characteristics of the ground station receiver, as long as the arrival times of user services using the same spreading code are staggered within the collision interval, they can be successfully captured by the receiver. Theoretically, the collision interval is the first two slice times after each bit of information is spread. In this embodiment, t is calculated.j Let t be the arrival time of target user j, j∈{1,2,...,N}. n (n∈{1,2,K,N},n≠j) represents the arrival time of other users, t chip For each slice time, conforming to |t n -t j |≤2·t chip The user is a conflicting user, and the user ID is recorded, forming the set N of conflicting users. C .

[0102] In this embodiment, for all users N, it is determined whether their service arrival time causes multi-access interference and conflict to the target user, forming a multi-access interference user set N. MAI and the set of conflicting users N C This serves as the basis for calculating interference power and optimizing the performance of satellite communication systems.

[0103] like Figure 4 As shown, in the spread spectrum telemetry and control system, the spreading factor is S, that is, 1 bit is spread by S times to form an S-slice signal. Theoretically, the first two slices of each bit are the conflict interval. Short messages that overlap with the target user in time and fall into the conflict interval are marked as conflicting users.

[0104] like Figure 5 As shown, if the short message sent by user 2 falls within the conflict window of user 1, it is marked as a conflicting user; although the short message sent by user 3 overlaps with that of user 1 in time, it is marked as a multiple access interference user because it does not fall within the conflict window.

[0105] The interference power calculation module is used to calculate the total multiple access interference power of the multiple access interference user to the target user according to the first influence condition, calculate the total conflict power of the conflicting user to the target user according to the second influence condition, and calculate the interference power of multiple access interference and conflict to the target user by superimposing them.

[0106] Specifically, the first influencing condition includes the overlap length, spreading code correlation, interfering user location, and interfering user transmission power; the second influencing condition includes the interfering user location and interfering user transmission power. By comprehensively considering the impact of multiple access interference and collisions on the target user, the total multiple access interference power caused by users in the multiple access interference user set to the target user, and the total collision power caused by users in the collision user set to the target user, are calculated separately, serving as the basis for user capacity statistics.

[0107] In this embodiment, the total multiple access interference power P of the multiple access interference user to the target user is calculated using the following logic. MAI :

[0108]

[0109] Among them, Pr p Let p be the signal power received by the high-orbit satellite from the p-th low-orbit satellite, where p∈N. MAI , ρ pj Let E[|ρ] be the normalized cross-correlation function of the spreading codes for user p and target user j. pj | 2 ] is |ρ pj | 2 The expected value, for pseudo-random codes such as Gold codes and m-sequences, is E[|ρ pj | 2 ]≈1 / 3S, where S is the spreading factor.

[0110] In this embodiment, there is no spreading gain during a collision; therefore, the total collision power is a direct sum of the powers of the colliding users. The total collision power P of the colliding users to the target user is calculated using the following logic. C :

[0111]

[0112] Among them, Pr q Let be the signal power received by the high-orbit satellite from the q-th low-orbit satellite, where q∈N. C .

[0113] The user capacity statistics module is used to calculate the signal-to-noise ratio (SNR) of the target user and to count the user capacity. Specifically, it calculates the SNR of the target user without interference and the SNR of the target user with superimposed interference power; wherein, the SNR of the target user j with superimposed interference power is represented by the following logic:

[0114]

[0115] Among them, Pr j The high-orbit satellite receives the signal power from target user j; P noise P is the noise power. noise = N0·B, where N0 is the noise power spectral density, taken as -174 dBm / Hz at room temperature, and B is the baseband bandwidth after despreading. In this embodiment, the signal-to-noise ratio (SNR) of the target user under interference-free conditions can be directly calculated using existing techniques.

[0116] Furthermore, a signal-to-noise ratio (SNR) reduction threshold ΔSNR is set. If SNR-SINR≥ΔSNR, the target user's short message transmission is deemed a failure. The simulation is repeated M times, and the number of short message transmission failures m is counted to calculate the target user's short message transmission success rate. Obtain the system's short message transmission success rate under different user capacities.

[0117] like Figure 6To illustrate the relationship between user capacity and access success rate in this embodiment, the main simulation parameters are set as follows:

[0118] 1) Low Earth Orbit Satellite System Model: Walker constellation, orbital altitude 2000km;

[0119] 2) Operating frequency: 27GHz;

[0120] 3) Business model: Poisson distribution, parameter set to 0.05;

[0121] 4) Transmission power: If the target user's power is 20dBW, while the power of other users is randomly distributed between 20dBW and 30dBW, then it is determined that the transmission power control capability is not available.

[0122] 5) High-orbit satellite antenna: 64-element planar array;

[0123] 6) Spreading factor S: 1023;

[0124] 7) Signal-to-noise ratio (SNR) drop threshold ΔSNR: 2dB.

[0125] In summary, this invention is applicable to the user capacity simulation calculation of low-Earth orbit (LEO) satellites (GEO satellites, orbital altitude approximately 36,000 km) serving asynchronous code division multiple access spread spectrum communication systems, when the LEO satellites they serve (orbital altitude not exceeding 2,000 km) use the same spreading codeword to send short messages for return space-based access. After comprehensively considering factors such as user distribution, service model, power control, antenna model, and channel conditions in a realistic manner, a generalized space-based short message spread spectrum telemetry and control capacity simulation system is proposed. This system can simulate and calculate the core key indicator of user capacity before the construction of complex systems such as GEO and LEO satellite constellations, evaluate the rationality of system design, and thus improve the scientific nature of decision-making during system construction and reduce system construction risks. The parameters within the simulation system can be dynamically configured according to the system design, demonstrating promising application prospects.

[0126] like Figure 2 As shown, this invention also provides a general capacity simulation method based on space-based short message spread spectrum telemetry and control. Addressing the user capacity assessment problem in multiple access systems, it provides a general simulation method comprising the following steps:

[0127] S1 simulates the number and location distribution of user satellites, specifically:

[0128] S1.1, Based on the construction requirements of the low-Earth orbit user constellation configuration, determine the number of users N and the orbital parameters of each user.

[0129] Specifically, the constellation configuration is the Walker constellation, and the orbital parameters include the semi-major axis, eccentricity, orbital inclination, right ascension of the ascending node, argument of perigee, and true anomaly.

[0130] S1.2, In the simulation system, the position and velocity of the user satellite are dynamically modeled. Based on the mobility of the user satellite, the position of the user satellite changes with time and moves along its orbit. The user position in the spherical coordinate system is denoted as... With the center of the sphere as the origin, where r i θ represents the distance from the user satellite to the origin. i This represents the azimuth angle of the user satellite in the xy plane. This represents the angle (elevation angle) between the user star and the z-axis, where i = 1, 2, ..., N.

[0131] User satellites refer to satellites that serve end users, responsible for receiving and transmitting user data, or acting as intermediaries between ground stations and satellite networks to achieve signal transmission. In this embodiment, the simulation system is specifically [specifically, a system described in the original text].

[0132] S2, establish a user satellite short message service model, and simulate service arrival times for all user satellites, specifically:

[0133] S2.1 Establish a business model; In this embodiment, each user can be modeled individually based on the actual business characteristics of the user star, or a unified business model can be adopted for all users.

[0134] S2.2, simulate the service arrival time of all user satellites according to the service model. The accuracy of the service arrival time is determined according to the system spreading code rate, which serves as the basic basis for judging interference and conflict between user satellites.

[0135] The specific arrival time of the simulated satellite service for all users is as follows:

[0136] Within time T, the arrival time of each user satellite is t. n Let n = 1, 2, ..., N, and let t1 = 0. Then the arrival time t of the nth user is... n The calculation formula is:

[0137] t n =t n-1 +Δt

[0138] Where Δt represents the interval between the arrival times of services from two adjacent user satellites, t n-1 This represents the arrival time of the (n-1)th user.

[0139] In this embodiment, the Poisson distribution model is used as an example for illustration. Since the arrival time of services from two user satellites follows a Poisson distribution, the interval between their arrival times follows an exponential distribution with parameter λ, where λ is the probability parameter representing the average number of events occurring per unit time. Therefore, Δt follows an exponential distribution with parameter λ. In this embodiment, an inverse transformation sampling method can be used to generate an exponentially distributed random number from uniformly distributed random numbers. The following logic represents Δt:

[0140] Δt=-log(1-rand) / λ

[0141] Here, rand means to generate uniformly distributed random numbers in the range [0,1), and 1-rand means to restrict the range to the range [0,1) to avoid infinity when taking the logarithm.

[0142] S3, based on the user satellite engineering model, determine whether the user satellite has transmit power control capability and set the transmit power, specifically as follows:

[0143] If the user satellite has the capability to control the transmission power, it can adjust the transmission power according to the link budget, balance the near-far effect, reduce the interference of high-power signals at the near end to low-power signals at the far end, and improve the overall user experience and system capacity.

[0144] If the user satellite does not have the capability to control transmission power, then the power value should be fixed according to the actual power value.

[0145] Furthermore, when the user satellite has the capability to control its transmission power, the transmission power value of the user satellite is adjusted according to the link budget so that the transmission power value is consistent with the signal power between users when the satellite is in high orbit, thus avoiding the suppression of low-power signals by high-power signals and the generation of near-far effects; when the user satellite does not have the capability to control its transmission power, the transmission power value of the user satellite is set according to the actual situation.

[0146] The adjustment of the user satellite's transmit power based on the link budget specifically involves the following strategy when the user satellite has transmit power control capabilities: The transmit power can be adjusted according to the following strategy, using the following logic to represent the signal power Pr received by the high-orbit satellite from the nth low-orbit satellite. n :

[0147] Pr n =Pt n ·Gt n ·Gr n ·L p ·L n

[0148] Among them, Pt n The launch power of the nth low-Earth orbit satellite needs to be adjusted; Gt n Gr represents the transmit antenna gain of the nth low-Earth orbit satellite.n The gain of the high-orbit satellite receiving antenna is related to the position of the low-orbit satellite. Generally, the farther the low-orbit satellite is from the high-orbit satellite, the larger the beam scanning angle of the high-orbit satellite's phased array antenna, and the lower the receiving antenna gain. The specific gain value can be obtained in step S4; L p The path loss is expressed as λ′ is the signal wavelength, d n L represents the distance from the nth low-Earth orbit satellite to the high-Earth orbit satellite. n Other losses, including atmospheric attenuation and pointing error, can be set based on engineering experience.

[0149] When a low-Earth orbit satellite reaches the location of a high-Earth orbit satellite, its transmission power reaches the level of the inter-user signal power Pr when the high-Earth orbit satellite is in orbit. n If all values ​​are Pr, then the transmit power Pt of each low-Earth orbit satellite can be calculated using the following logic. n :

[0150]

[0151] S4: Model the phased array antenna of the high-orbit satellite based on the antenna parameters, and then execute S5.

[0152] Specifically, the antenna parameters include antenna element type, operating frequency band, number of antenna elements, and antenna element spacing. The simulation calculation results include antenna performance such as antenna gain considering beam scanning loss. The simulation calculation results after modeling are used as design inputs and sent to step S5. In this embodiment, the antenna gain Gr received by the high-orbit satellite under beam scanning loss is calculated using the following strategy. n :

[0153] For the two-dimensional planar phased array antennas commonly used in high-orbit satellites, their beam scanning reaches... Gain at time Using the following logical representation:

[0154]

[0155] in, N represents the elevation and azimuth angles of the beam pointing. x N represents the number of antenna elements in the x-direction. y G represents the number of antenna elements in the y-direction; element η is the gain of a single antenna element; η is the antenna array efficiency (including feed loss, impedance matching, etc., usually taken as 0.7 to 0.9); For two-dimensional array factors; cos a θ is the scanning loss, and a is an empirical exponent, which is affected by array mutual coupling, edge effects, etc., and is usually taken as 1 to 1.5. (Two-dimensional array factor) Using the following logical representation:

[0156]

[0157] Where k is the wave number, expressed as k = 2π / λ′. d x and d y The unit spacing is defined as the x-axis and y-axis spacing.

[0158] S5. Based on the user's location and link conditions, simulate all user channels and calculate the received power Pr of the user satellite signal reaching the high-orbit satellite at different locations. n The link conditions include the operating frequency band f = c / λ′ and the antenna gain considering scanning loss. Path loss L p Other losses L n wait.

[0159] In this embodiment, by simulating all user channels, the received power of user satellite signals at different locations reaching the high-orbit satellite is calculated, which serves as the basic basis for calculating interference power and collision power.

[0160] S6, select the target user location, simulate user capacity, and perform multi-access interference and conflict determination based on service arrival time, specifically:

[0161] S6.1 Select the target user location and simulate user capacity; This implementation prioritizes coverage edges and simulates the worst-case conditions, assuming that the target user is located at the edge of the coverage area of ​​the high-orbit satellite; At this time, the path loss and antenna scanning loss of the target user are relatively large, and the simulated user capacity is the case under poor conditions. Therefore, the user capacity will be improved when the target user is located in other locations.

[0162] S6.2, determine whether other users cause multi-address interference and conflict to the target user based on the arrival time of the user's satellite service. If so, record the set of multi-address interference users and the set of conflicting users.

[0163] When the timeline of the arrival time of other users' services overlaps with that of the target user, it is determined that other users are causing multi-address interference to the target user. The user IDs that are causing multi-address interference to the target user are recorded as the set of multi-address interference users.

[0164] When the arrival time of the target user's service falls within the conflict interval and overlaps with the timeline of the arrival time of other users' services, it is determined that other users have caused a conflict with the target user. The user IDs that caused the conflict with the target user are recorded, forming a set of conflicting users.

[0165] In this embodiment, based on the arrival time of the user's satellite service, it is determined whether other users cause multiple access interference and conflict to the target user. On the one hand, multiple access interference will be generated between short message signals that overlap on the arrival time axis. The user numbers that cause multiple access interference to the target user are recorded, forming the multiple access interference user set N. MAI On the other hand, there is a possibility of signal collisions between short user messages sharing the code channel. Thanks to the delay capture characteristics of the ground station receiver, as long as the arrival times of user services using the same spreading code are staggered within the collision interval, they can be successfully captured by the receiver. Theoretically, the collision interval is the first two slice times after each bit of information is spread. In this embodiment, t is calculated. j Let t be the arrival time of target user j, j∈{1,2,...,N}. n (n∈{1,2,K,N},n≠j) represents the arrival time of other users, t chip For each slice time, conforming to |t n -t j |≤2·t chip The user is a conflicting user, and the user ID is recorded, forming the set N of conflicting users. C .

[0166] For all users N, determine whether their service arrival time causes multi-access interference and conflict to the target user, forming a multi-access interference user set N. MAI and the set of conflicting users N C This serves as the basis for calculating interference power and optimizing the performance of satellite communication systems.

[0167] S7. Calculate the total multiple access interference power of the multiple access interference user to the target user according to the first influence condition, calculate the total conflict power of the conflicting user to the target user according to the second influence condition, and calculate the interference power of multiple access interference and conflict to the target user by superimposing them.

[0168] Specifically, the first influencing condition includes the overlap length, spreading code correlation, interfering user location, and interfering user transmission power; the second influencing condition includes the interfering user location and interfering user transmission power. By comprehensively considering the impact of multiple access interference and collisions on the target user, the total multiple access interference power caused by users in the multiple access interference user set to the target user, and the total collision power caused by users in the collision user set to the target user, are calculated separately, serving as the basis for user capacity statistics.

[0169] In this embodiment, the total multiple access interference power P of the multiple access interference user to the target user is calculated using the following logic. MAI :

[0170]

[0171] Among them, Pr pLet p be the signal power received by the high-orbit satellite from the p-th low-orbit satellite, where p∈N. MAI , ρ pj Let E[|ρ] be the normalized cross-correlation function of the spreading codes for user p and target user j. pj | 2 ] is |ρ pj | 2 The expected value, for pseudo-random codes such as Gold codes and m-sequences, is E[|ρ pj | 2 ]≈1 / 3S, where S is the spreading factor.

[0172] In this embodiment, there is no spreading gain during a collision; therefore, the total collision power is a direct sum of the powers of the colliding users. The total collision power P of the colliding users to the target user is calculated using the following logic. C :

[0173]

[0174] Among them, Pr q Let be the signal power received by the high-orbit satellite from the q-th low-orbit satellite, where q∈N. C .

[0175] S8, calculate the signal-to-noise ratio of the target user and calculate the user capacity, including the following steps:

[0176] S81, calculate the signal-to-noise ratio (SNR) of the target user when there is no interference, and the signal-to-interference-plus-noise ratio (SINR) of the target user when interference power is added; wherein, the SINR of the target user j when interference power is added is expressed by the following logic:

[0177]

[0178] Among them, Pr j The high-orbit satellite receives the signal power from target user j; P noise P is the noise power. noise = N0·B, where N0 is the noise power spectral density, taken as -174 dBm / Hz at room temperature, and B is the baseband bandwidth after despreading. In this embodiment, the signal-to-noise ratio (SNR) of the target user under interference-free conditions can be directly calculated using existing techniques.

[0179] S82, set a signal-to-noise ratio (SNR) drop threshold ΔSNR. If SNR - SINR ≥ ΔSNR, then the target user's short message transmission is considered a failure. Simulate M times, count the number of short message transmission failures m, and calculate the target user's short message transmission success rate. Obtain the system's short message transmission success rate under different user capacities.

[0180] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A general capacity simulation system based on space-based short message spread spectrum telemetry and control, characterized in that, include: The user distribution simulation module is used to simulate the number and location distribution of user satellites. The short message service generation module is used to establish a service model and simulate the service arrival time for all users. The transmit power control module is used to determine whether the user satellite has transmit power control capability and set the transmit power according to the user satellite engineering model; The high-orbit satellite antenna simulation module is used to model the phased array antenna of a high-orbit satellite based on the antenna parameters and send the simulation calculation results to the star-ground channel simulation module. The satellite-to-ground channel simulation module is used to simulate all user channels based on user locations and link conditions, and to calculate the received power of user satellite signals reaching the high-orbit satellite at different locations. The multiple access interference and conflict determination module is used to select the target user location and simulate user capacity, and perform multiple access interference determination and conflict determination based on the arrival time of user satellite services. The interference power calculation module is used to calculate the total multiple access interference power of the multiple access interference user to the target user according to the first influence condition, calculate the total conflict power of the conflicting user to the target user according to the second influence condition, and calculate the interference power of multiple access interference and conflict to the target user by superimposing them. The user capacity statistics module is used to calculate the signal-to-noise ratio of the target user and to count the user capacity.

2. The general capacity simulation system based on space-based short message spread spectrum telemetry and control according to claim 1, characterized in that, The user distribution simulation module specifically determines the number of users N and the orbital parameters of each user based on the construction requirements of the low-Earth orbit user constellation configuration. The position and velocity of the user satellite are dynamically modeled in the simulation system. Based on the user satellite's mobility, the position of the user satellite changes with time as it moves along its orbit. The user position is denoted as in the spherical coordinate system. The center of the sphere is the origin; where r i θ represents the distance from the user satellite to the origin. i This represents the azimuth angle of the user satellite in the xy plane. This represents the angle between the user star and the z-axis, where i = 1, 2, ..., N.

3. The general capacity simulation system based on space-based short message spread spectrum telemetry and control according to claim 1, characterized in that, The short message service generation module specifies the arrival time of the simulated service for all users as follows: Within time T, the arrival time of each user satellite is t. n Let n = 1, 2, ..., N, and let t1 = 0. Then the arrival time t of the nth user is... n The calculation formula is: t n =t n-1 +Δt Where Δt represents the interval between the arrival times of services from two adjacent user satellites, t n-1 This represents the arrival time of the (n-1)th user.

4. The general capacity simulation system based on space-based short message spread spectrum telemetry and control according to claim 3, characterized in that, The arrival time of the service follows a Poisson distribution model. Therefore, the interval between the arrival times of the two user satellite services follows an exponential distribution with parameter λ, where λ is the distribution probability parameter representing the average number of events occurring per unit time. Thus, Δt follows an exponential distribution with parameter λ. Using the inverse transformation sampling method, uniformly distributed random numbers are used to generate exponentially distributed random numbers. The following logic represents Δt: Δt=-log(1-rand) / λ Where rand means to generate uniformly distributed random numbers in the range [0,1), and 1-rand means to restrict the range to the range [0,1).

5. The general capacity simulation system based on space-based short message spread spectrum telemetry and control according to claim 1, characterized in that, The transmission power is specifically set in the transmission power control module as follows: If the user satellite has transmit power control capability, the transmit power is adjusted according to the link budget to balance the near-far effect; if the user satellite does not have transmit power control capability, the transmit power is fixed according to the actual power value; wherein, adjusting the user satellite transmit power value according to the link budget specifically means: The following logic can be used to represent the signal power Pr received by a high-orbit satellite from the nth low-orbit satellite. n : Pr n =Pt n ·Gt n ·Gr n ·L p ·L n Among them, Pt n Let Gt be the launch power of the nth low-Earth orbit satellite. n For the transmit antenna gain of the nth low-Earth orbit satellite, Gr n For the gain of the high-orbit satellite receiving antenna, L p The path loss is expressed as λ′ is the signal wavelength, d n Let L be the distance from the nth low-Earth orbit satellite to the high-Earth orbit satellite. n Other losses.

6. The general capacity simulation system based on space-based short message spread spectrum telemetry and control according to claim 1, characterized in that, The multiple access interference and conflict determination module performs multiple access interference determination and conflict determination as follows: When the timeline of the arrival time of other users' services overlaps with that of the target user, it is determined that other users are causing multi-address interference to the target user. The user IDs that are causing multi-address interference to the target user are recorded as the set of multi-address interference users. When the arrival time of the target user's service falls within the conflict interval and overlaps with the timeline of the arrival time of other users' services, it is determined that other users have caused a conflict with the target user. The user IDs that caused the conflict with the target user are recorded, forming a set of conflicting users.

7. The general capacity simulation system based on space-based short message spread spectrum telemetry and control according to claim 1, characterized in that, The first influencing condition in the interference power calculation module includes the overlap length, spreading code correlation, interference user location, and interference user transmission power; the second influencing condition includes the interference user location and interference user transmission power. The total multiple access interference power P from the multiple access interference user to the target user is calculated using the following logic. MAI : Among them, Pr p Let p be the signal power received by the high-orbit satellite from the p-th low-orbit satellite, where p∈N. MAI N MAI For the set of multiple access interference users, ρ pj Let E[|ρ] be the normalized cross-correlation function of the spreading codes for user p and target user j. pj | 2 ] is |ρ pj | 2 Expected value; There is no spreading gain during a collision; therefore, the total collision power is a direct sum of the powers of the colliding users. The total collision power P of the colliding users to the target user is calculated using the following logic. C : Among them, Pr q Let be the signal power received by the high-orbit satellite from the q-th low-orbit satellite, where q∈N. C N C For the set of conflicting users.

8. The general capacity simulation system based on space-based short message spread spectrum telemetry and control according to claim 7, characterized in that, The user capacity statistics module calculates the signal-to-noise ratio (SNR) of the target user by calculating the SNR of the target user without interference and the signal-to-interference-plus-noise ratio (SINR) of the target user with superimposed interference power. The SINR of the target user j with superimposed interference power is represented by the following logic: Among them, Pr j The high-orbit satellite receives the signal power of target user j, P noise P is the noise power. noise =N0·B, where N0 is the noise power spectral density, B is the baseband bandwidth after despreading, and P C P represents the total conflict power between conflicting users and the target user. MAI This represents the total multiple access interference power from multiple access interference users to the target user.

9. The general capacity simulation system based on space-based short message spread spectrum telemetry and control according to claim 8, characterized in that, The user capacity statistics module specifically calculates user capacity as follows: A signal-to-noise ratio (SNR) drop threshold ΔSNR is set. If SNR - SINR ≥ ΔSNR, the target user's short message transmission is deemed a failure. The simulation is repeated M times, and the number of short message transmission failures (m) is counted to calculate the target user's short message transmission success rate. Obtain the system's short message transmission success rate under different user capacities.

10. A general capacity simulation method based on space-based short message spread spectrum telemetry and control, characterized in that, Includes the following steps: S1 simulates the number and location distribution of user satellites; S2, Establish a user star short message service model and simulate service arrival time for all user stars; S3, based on the user satellite engineering model, determine whether the user satellite has the capability to control transmission power and set the transmission power; S4, Model the phased array antenna of the high-orbit satellite based on the antenna parameters, and then execute S5; S5. Based on the user's location and link conditions, simulate all user channels and calculate the received power of user satellite signals at different locations reaching the high-orbit satellite. S6, Select the target user location, simulate user capacity, and determine multiple access interference and conflict based on service arrival time; S7. Calculate the total multiple access interference power of the multiple access interference user to the target user according to the first influence condition, calculate the total conflict power of the conflicting user to the target user according to the second influence condition, and calculate the multiple access interference and conflict interference power to the target user by superimposing them. S8 calculates the signal-to-noise ratio of the target user and counts the user capacity.

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