A low earth orbit satellite hop beam pattern design method based on precoding

Abstract

This invention relates to a method for designing hopping beam patterns for low-Earth orbit (LEO) satellites based on precoding. The purpose of this invention is to solve the problem of hopping beam pattern design in LEO satellite systems. The specific process of the method is as follows: An LEO multi-beam satellite system model includes users, LEO satellites, and a ground gateway; users transmit their communication capacity requirements to the LEO satellites via the uplink, and the LEO satellites send communication capacity requirement requests to the ground gateways via the feed link; the ground gateways allocate time slot resources according to the communication capacity requirement requests; the specific process is as follows: 1. Obtain the downlink precoding matrix; 2. Calculate the signal-to-interference-plus-noise ratio (SINR) and capacity based on the precoding matrix and the channel matrix; 3. Design the hopping beam pattern based on pseudo-random codes, i.e., obtain the final result of time slot resource allocation. This invention is applicable to the field of aerospace technology.

Description

Technical Field

[0001] This invention relates to the field of aerospace technology, and in particular to a method for designing low-Earth orbit satellite hopping beam patterns based on precoding. Background Technology

[0002] The 3rd Generation Partnership Project (3GPP) provides a clear scenario definition for Non-terrestrial Networks (NTNs) and proposes the coordinated development and integration of terrestrial, satellite, and drone networks. NTNs, as an important supplement to terrestrial cellular mobile communications, can provide wide-area coverage regardless of terrain. Satellite communications, as an indispensable part of the integrated air-space-ground system, are of significant strategic importance for research. Low Earth Orbit (LEO) satellite systems can achieve global coverage. Compared to medium and high Earth Orbit satellites, LEO satellites offer numerous advantages, including lower launch costs, lower latency in communication with terrestrial systems, lower link loss, and more flexible networking methods, meeting the future global terminal access needs anytime, anywhere. Therefore, they have become a key focus of next-generation network research.

[0003] Traditional single-beam satellite systems use a single wide beam to cover ground users. However, due to limitations in channel capacity and power, this is insufficient to meet the enormous service demands of current satellite communications. Most existing satellite systems employ multi-beam antennas to generate multiple spot beams with higher gain and smaller beam angles to cover the same area, and use frequency reuse and other methods between different beams to reduce the impact of co-channel interference.

[0004] However, services in the coverage area are often unevenly distributed. The fixed resource allocation of multiple beams means that beams in hotspot areas cannot meet user needs, while beam resources in non-hotspot areas are often excessive, resulting in low resource utilization and severely impacting the system performance ceiling of LEO satellites. To meet the growing communication needs of ground terminals, in recent years, LEO satellites have begun to adopt beam-hopping technology to improve the overall system performance and functionality. This technology utilizes all available onboard resources and provides services to different ground cells at different times by changing the pointing of the onboard antennas and the combination of beams.

[0005] As a key technology in the field of dynamic beam scheduling, beam hopping technology can be regarded as a time slot resource allocation problem. Due to the different geographical location of the cell, downlink channel conditions and terminal service requests, different frequency reuse schemes are adopted, and the size of time slot resources allocated to each beam is also different. Therefore, it is necessary to design corresponding resource scheduling algorithms to improve resource utilization and thus meet the unbalanced and uneven communication needs of ground terminals. Summary of the Invention

[0006] The purpose of this invention is to address the problems in beam hopping pattern design for low-Earth orbit (LEO) satellite systems. These problems include: uneven distribution of services in the sub-satellite coverage area; fixed resource allocation for multiple beams leading to insufficient beam resources in hotspot areas while non-hotspot areas often have excess resources, resulting in low resource utilization and severely impacting the system performance ceiling of LEO satellites; and the fact that LEO satellites, due to their smaller size and limited payload capacity, are typical resource-constrained systems, making most beam scheduling schemes applicable to GEO satellites unsuitable and causing uneven resource allocation. Therefore, this invention proposes a precoding-based beam hopping pattern design method for LEO satellites.

[0007] The design problems of hopping beam patterns in low-Earth orbit (LEO) satellite systems are as follows: services in the sub-satellite coverage area are often unevenly distributed. The fixed resource allocation of multiple beams means that beams in hotspot areas cannot meet user needs, while beam resources in non-hotspot areas are often excessive, resulting in low resource utilization and seriously affecting the upper limit of LEO satellite system performance. In addition, due to their smaller size and more limited payload capacity, LEO satellites are typical resource-constrained systems, and most beam scheduling schemes used in GEO satellites are not applicable, resulting in uneven resource allocation.

[0008] The specific process of a precoding-based method for designing low-Earth orbit satellite hopping beam patterns is as follows:

[0009] The LEO multibeam satellite system model includes users, LEO satellites, and ground gateways;

[0010] Users transmit their communication capacity requirements to the LEO satellite via the uplink. The LEO satellite then sends a communication capacity requirement request to the ground gateway via the feeder link. The ground gateway allocates time slot resources based on the communication capacity requirement request.

[0011] The specific process is as follows:

[0012] Step 1: Obtain the downlink precoding matrix;

[0013] Step 2: Calculate the signal-to-interference-plus-noise ratio (SINR) and capacity based on the precoding matrix and channel matrix;

[0014] Step 3: Design hopping beam patterns based on pseudo-random codes to obtain the final result of time slot resource allocation.

[0015] Invention effects:

[0016] This invention first analyzes the main problems arising when low-Earth orbit (LEO) multi-beam satellites simultaneously provide services to multiple cells. To increase spectrum resource utilization, significant inter-beam interference occurs between adjacent beams. The relative positional relationship between LEO satellites and ground cells is time-varying; satellites travel at high speeds, with overhead transit times of only a few minutes, unlike traditional GEO multi-beam satellites which can continuously provide service to the same area during their orbital period. Furthermore, LEO satellites, due to their smaller size and more limited payload capacity, are typical resource-constrained systems, making most beam scheduling schemes applicable to GEO satellites unsuitable. Therefore, before designing a beam-hopping scheme, the system architecture foundation for subsequent resource allocation schemes is first established, a model of the LEO multi-beam satellite system is created, the actual coverage scenario of the LEO satellite is given, and a time-slot resource model is established.

[0017] Next, referencing the concept of terrestrial MIMO systems, the downlink of a multi-beam satellite is modeled as a MIMO channel. Completely different from existing satellite network architectures, space MIMO systems in LEO scenarios can enhance spectral efficiency compared to traditional transmission methods, increasing information transmission rates by utilizing diversity and multiplexing gains. Based on these principles, MIMO systems can be practically applied to satellite communications. Under ideal channel conditions, by designing suitable transmit signals to make the downlink channel vectors mutually orthogonal, inter-beam interference in space is completely eliminated, and the satellite channel capacity increases linearly with the number of transmit or receive antennas. To ensure that the complexity on the satellite side remains within an acceptable range, it is assumed that the on-board payload of the LEO satellite is based on a bent-tube architecture, i.e., no signal processing is performed. The content transmitted to the ground cell via the downlink is transmitted through spatial multiplexing between different data streams in the beam. The precoding matrix is ​​calculated based on the channel state information. Although the precoding method at the transmitter requires certain resources to feedback the link's channel state information, its impact on the overall system is small, and in fixed satellite services, the precoding method can significantly improve gain, while the gain brought by multi-user detection technology is very limited. Therefore, in order to reduce the overhead of the hopping beam ground terminal, this invention uses the channel state information transmitted via the reverse link and calculates it at the ground gateway, and then uses a precoding scheme at the satellite transmitter end to avoid downlink interference.

[0018] Finally, a hopping beam pattern design based on a precoding scheme and beam spatial isolation is presented. A hopping beam pattern is essentially a set of ground cells illuminated within a time slot. The same point beam can cover different ground cells in different time slots according to a scheduling scheme to form a hopping beam pattern, ultimately achieving flexible resource allocation. Attached Figure Description

[0019] Figure 1 Model of a low-Earth orbit multibeam satellite system;

[0020] Figure 2 A schematic diagram illustrating the partitioning of time slot resources in the model;

[0021] Figure 3 This is a schematic diagram of the satellite's coverage area;

[0022] Figure 4 A diagram showing the relative geometric positions of ground cells and satellites;

[0023] Figure 5 The graphs show the relationship between signal-to-noise ratio (SNR) and signal-to-interference-plus-noise ratio (SINR) as a function of inter-cell distance.

[0024] Figure 6 Diagram of wave position division model;

[0025] Figure 7 Result diagram of beam skipping pattern design;

[0026] Figure 8 A diagram showing the results of allocating communication capacity and communication capacity requirements to each cell. Detailed Implementation

[0027] Specific Implementation Method 1: The specific process of this implementation method for designing low-Earth orbit satellite hopping beam patterns based on precoding is as follows:

[0028] The LEO multibeam satellite system model includes users, LEO satellites, and ground gateways;

[0029] Users transmit their communication capacity requirements to the LEO satellite via the uplink. The LEO satellite then sends a communication capacity requirement request to the ground gateway via the feeder link. The ground gateway allocates time slot resources based on the communication capacity requirement request.

[0030] The specific process is as follows:

[0031] Step 1: Obtain the downlink precoding matrix;

[0032] Step 2: Calculate the signal-to-interference-plus-noise ratio (SINR) and capacity based on the precoding matrix and channel matrix;

[0033] Step 3: Design hopping beam patterns based on pseudo-random codes to obtain the final result of time slot resource allocation.

[0034] Satellite system model such as Figure 1As shown, the LEO satellite first divides the coverage area and summarizes the needs of all ground users to obtain the service demand size of each cell. The service demand size of each cell is sent to the LEO satellite through the uplink and then sent to the ground gateway through the feeder link. The gateway formulates an appropriate beam hopping strategy and resource allocation algorithm based on the service demand size of each band and the downlink channel conditions, and then sends the allocation result to the LEO satellite through the downlink. The satellite's multi-beamforming algorithm schedules the beams to meet the service demand of each cell, completing the dynamic allocation of resources in dimensions such as time slots, frequencies, and beams.

[0035] Time slot resource model such as Figure 2 As shown, hopping beams allocate different amounts of time resources to different beam positions using the time-slicing principle, which is equivalent to the beam jumping to different coverage locations. By flexibly allocating resources such as time slots, the total throughput of the system is maximized, and the communication needs of different cells are met to the greatest extent.

[0036] The present invention is subject to the following interference:

[0037] Based on the LEO multi-beam satellite system model, the impact of co-channel interference caused by the simultaneous use of multiple beams is analyzed;

[0038] Satellite coverage area diagram as shown Figure 3 As shown, the geometric relationship diagram of the ground cells is as follows: Figure 4 As shown, the distance d between cells A and C is obtained from the arc length calculation formula, and the expression is:

[0039]

[0040] In the formula, θ is the central angle, and R e The radius of the Earth;

[0041] Since downlink interference affects the overall system channel capacity, the relationship between the receiver-side interference signal strength [I] and the inter-cell distance d is analyzed; the specific process is as follows:

[0042] By solving for the distance d between the user's location and the nadir point, and the distance R between the user's location and the satellite, the downlink link budget of the satellite is finally obtained (Formulas 6, 7, and 8).

[0043] First, calculate the downlink link loss [L] of the LEO satellite system:

[0044] [L] = 32.45 + 20log 10 (r / 103)+20log 10 (f / 106)

[0045] In the formula, r is the distance between satellite and ground, and f is the downlink frequency;

[0046] Calculate the signal-to-noise ratio (SNR) at each beam position under ideal conditions and the receiver-side signal-to-interference-plus-noise ratio (SINR) under conditions of co-channel interference between the two beams:

[0047]

[0048]

[0049] In the formula, [P T [G] represents the transmit power in dB. T [This refers to the transmit antenna gain in dB.] The receiver-side quality factor is expressed in dB. The noise temperature of the receiver (ground). P is the Boltzmann constant in dB, and [B] is the link bandwidth in dB; T G is the transmission power measured in watts (W). T (0) is the transmit antenna gain in watts (W) with an off-axis angle of 0. R (0) represents the receiving antenna gain in watts (W) with an off-axis angle of 0°, λ is the electromagnetic wave wavelength, and G T (β) is the transmit antenna gain in W (watts) with an off-axis angle of 0, and N is the noise power; β is the off-axis angle of the line connecting cell A and cell C to the satellite;

[0050] Based on the above calculation formulas, the relationship curves between signal-to-noise ratio, signal-to-interference-plus-noise ratio, and co-frequency reuse distance d are plotted, as shown below. Figure 5 As shown; taking a cell radius r of 15km, as the distance d increases, the interference between the simultaneously lit beams gradually decreases. When the distance between two users on the ground is 5 times the cell radius, the influence of interference signals from other cells on the target cell can be ignored, and the signal-to-noise ratio is approximately equal to the signal-to-interference-plus-noise ratio.

[0051] Specific Implementation Method Two: This implementation method differs from Specific Implementation Method One in that: the downlink precoding matrix is ​​obtained in step one; the specific process is as follows:

[0052] To address the co-channel interference problem, a downlink precoding matrix is ​​designed.

[0053] Most multi-beam satellite systems employ low-complexity linear precoding schemes, and their performance metrics are close to the theoretical upper limit obtained from nonlinear coding schemes. By sacrificing some feedback link overhead to obtain downlink channel state information, inter-beam interference in the downlink is reduced, thereby increasing the overall system capacity.

[0054] Step 11: Model the channel matrix of the low-Earth orbit satellite downlink MIMO link;

[0055] Steps 1 and 2: Obtain the downlink precoding matrix based on the channel matrix.

[0056] The other steps and parameters are the same as in Specific Implementation Method 1.

[0057] Specific Implementation Method Three: This implementation method differs from Specific Implementation Method One or Two in that: in step one, the channel matrix of the low-Earth orbit satellite downlink MIMO link is modeled.

[0058]

[0059] In the formula, G R d represents the receiver antenna gain in watts (W). k The distance from the satellite to the k-th ground cell. For noise power, For the noise temperature of the receiver (ground), a kp Let p be the gain from the p-th antenna on the satellite to the k-th ground cell. Channel matrix The element in the k-th row and p-th column represents the channel factor from the p-th antenna on the LEO satellite to the k-th ground cell; Boltzmann's constant is expressed in joules per kelvin.

[0060] The minimum mean square error (MMSE) precoding scheme adopted in this paper takes into account the interference between users and the channel noise, and minimizes the error between the original transmitted signal and the received signal. Regardless of whether the ambient noise of the channel is large or small, this precoding design can achieve good system performance.

[0061] Other steps and parameters are the same as in specific implementation method one or two.

[0062] Specific Implementation Method Four: This implementation method differs from Specific Implementation Methods One to Three in that: in steps one and two, the downlink precoding matrix is ​​obtained based on the channel matrix; the specific process is as follows:

[0063] Give the expression for the signal received at the receiver (ground).

[0064]

[0065] In the formula, s is the satellite transmitted signal vector. It is Gaussian white noise. Let T be the channel matrix and T be the precoding matrix;

[0066] The process of solving the precoding matrix T is as follows:

[0067] The precoding matrix T based on the minimum mean square error criterion is the optimal solution to the problem of minimizing the mean square error (MSE). The optimization problem is modeled and constraints are given:

[0068] trace(TT H )≤P

[0069] In the formula, P is the total available power limit on the satellite, H is the conjugate transpose, and trace is the trace of the matrix;

[0070] Thus, the expression for the precoding matrix based on the minimum mean square error (MMSE) is obtained:

[0071]

[0072] In the formula, I is the identity matrix (the dimension of the identity matrix I and the channel matrix). (Same dimensions), K is the total number of beams.

[0073] The other steps and parameters are the same as those in one of the specific implementation methods one to three.

[0074] Specific Implementation Method Five: This implementation method differs from Specific Implementation Methods One to Four in that: in step two, the signal-to-interference-plus-noise ratio (SINR) and capacity are calculated based on the precoding matrix and the channel matrix; the specific process is as follows:

[0075] Let h q and t q Channel matrix The q-th row and the q-th column of the precoding matrix T, where t represents the t-th time slot:

[0076]

[0077] In the formula, SINR q,t Let t be the downlink signal-to-interference-plus-noise ratio of the q-th beam in the t-th time slot. j The j-th column of the precoding matrix T;

[0078] The capacity of the nth ground cell corresponding to the qth beam is obtained based on the signal-to-interference-plus-noise ratio (SINR).

[0079]

[0080] In the formula, r n,t Let B be the capacity of the t-th time slot in the n-th cell, and let B be the link bandwidth in Hertz. n,t The beam lighting result for the nth cell in the tth time slot;

[0081] When x n,tWhen =1, it indicates that there is beam coverage, and the channel capacity is calculated according to Shannon's formula (14);

[0082] When x n,t When = 0, it indicates no beam coverage, meaning the cell throughput in that time slot is 0;

[0083] Capacity and beam hopping time slot T S Multiplying these together gives the throughput of each cell within time slot t:

[0084] C n,t =r n,t ·T S n = 1, 2, ..., N, t = 1, ..., N slot

[0085] In the formula, N slot N is the number of time slots for each window; N is the total number of cells.

[0086] like Figure 5 As shown, the throughput performance curves of MMSE precoding under different Rice factors in the low-Earth orbit satellite scenario designed in this paper are presented. The system throughput is maximized when the Rice factor is 1dB. Since the gain of the MIMO system comes from the diversity gain and multiplexing gain at both the transmitting and receiving ends, the larger the Rice factor, the stronger the direct path component of the signal, resulting in stronger signal correlation at the ground receiver and thus a smaller channel capacity.

[0087] The other steps and parameters are the same as those in specific implementation methods one through four.

[0088] Specific Implementation Method Six: This implementation method differs from Specific Implementation Methods One to Five in that: in step three, the time slot resource allocation is a hopping beam that allocates different amounts of time resources to different beam positions, which is equivalent to the beam jumping between different coverage locations;

[0089] The beam-hopping time window is defined as the length of time a region is stared at, defined as T. H ;

[0090] A hopping beam slot is the smallest unit for allocating time resources to different beam positions, defined as T. S ;

[0091] This gives us the number of time slots N for each window. slot :

[0092]

[0093] The other steps and parameters are the same as those in specific implementation methods one through five.

[0094] Specific Implementation Method Seven: This implementation method differs from Specific Implementation Methods One through Six in that: in step three, beam hopping pattern design is performed based on pseudo-random codes, thus obtaining the final result of time slot resource allocation; the specific process is as follows:

[0095] A skip beam pattern is a collection of ground-lit cells in a time slot;

[0096] Due to onboard payload limitations, each time slot can only cover a maximum of K cells, and the sum of the beams illuminated in each time slot must be less than the maximum number of beams that the satellite can provide:

[0097]

[0098] In the formula, N is the number of ground cells and K is the number of beams;

[0099] x t =[x 1，t x 2，t , ..., x N，t ]

[0100] In the formula, x t Let be the beam illumination vector of all cells under the single-satellite coverage in time slot t. The dimension of the beam illumination vector is equal to the number of ground cells.

[0101] Make x t Satisfy the following formula:

[0102] x′ t Ax t =0 t=1,…,N slot

[0103] In the formula, matrix A represents the proximity matrix for wavelength design, where adjacent cells are set to 1 and non-adjacent cells are set to 0; x′ t For x t Transpose of;

[0104] x that satisfies the above equation t The pattern set Y = [y1, y2, ..., y M There are 6 x's t Satisfying the condition Y = [y1, y2, ..., y6], a pseudo-random design of available patterns is implemented. For each time slot, a pattern is selected from Y, and the number of times each pattern is lit is defined as [l1, l2, ..., l...]. M (If the first pattern is selected in each of the two time slots, then the first pattern is selected twice, and l1 will be 2). The number of times the pattern is lit is a natural number. Since only one pattern is selected in each time slot, the sum of the number of times the pattern is lit is the number of time slots in the window; l M The number of times the Mth pattern is lit;

[0105] To further reduce the impact of inter-beam interference, a spatial isolation scheme based on beam allocation is first designed. Assuming that the satellite coverage area is divided into 24 cells in 6 rows and 4 columns, in order to increase the maximum information transmission rate, the spatial isolation scheme sets that adjacent beams cannot be lit at the same time.

[0106] The objective function is to maximize the minimum value of cell satisfaction, which is defined as the ratio of the communication capacity provided by the satellite to the communication capacity demand of the cell.

[0107] The beam skipping problem is modeled as a convex optimization problem and solved using simulation software.

[0108]

[0109]

[0110]

[0111]

[0112]

[0113] In the formula, ξ is the objective function, C1 is constraint 1, C2 is constraint 2, C3 is constraint 3, C4 is constraint 4, and R... n D represents the throughput provided by the satellite to the nth cell. n Let n be the communication capacity requirement of the nth cell. c is a natural number mn Let N be the element in the m-th row and n-th column of matrix C, N be the total number of cells, M be the total number of patterns, and P1 be question 1.

[0114] The final result of system resource allocation is obtained based on the number of times each pattern is lit. (For example, if pattern y1 is selected 3 times, then...) (y1 appears 3 times in the middle);

[0115] X is the hopping beam pattern within a hopping beam window length. The hopping beam pattern defines the set of cells illuminated in each time slot and is also regarded as the final result of system resource allocation.

[0116] The other steps and parameters are the same as those in specific implementation methods one through six.

[0117] The beneficial effects of the present invention are verified using the following embodiments:

[0118] Example

[0119] The simulation was conducted according to the specific implementation method. The simulation parameters were set as follows: carrier frequency of 20 GHz, bandwidth of 500 MHz, LEO multi-beam satellite antenna, Ricean channel model, ground beam radius of 15 km, random distribution of ground cell traffic size, and cell partitioning model as follows. Figure 6 As shown.

[0120] The simulation environment is: MATLAB R2017b

[0121] Simulation results are as follows Figure 7 As shown, the results of the hopping beam pattern design within 10 time slots are presented. White represents illuminated time slots, and black represents unilluminated time slots. It can be seen that adjacent beams are not illuminated simultaneously, conforming to the principle of preliminary spatial isolation. Furthermore, a comparison of the service provision size and demand capacity of each of the 24 cells is obtained, such as... Figure 8 As shown, by maximizing the minimum satisfaction value of the cell, the minimum satisfaction value is 0.8223, as shown in the pattern design results, thus completing the resource allocation scheme for beam skipping.

Claims

1. A method for designing low-Earth orbit satellite hopping beam patterns based on precoding, characterized in that: The specific process of the method is as follows: The LEO multibeam satellite system model includes users, LEO satellites, and ground gateways; Users transmit their communication capacity requirements to the LEO satellite via the uplink, and the LEO satellite sends the communication capacity requirement request to the ground gateway via the feeder link. The ground gateway allocates time slot resources based on communication capacity demand requests; The specific process is as follows: Step 1: Obtain the downlink precoding matrix; Step 2: Calculate the signal-to-interference-plus-noise ratio (SINR) and capacity based on the precoding matrix and channel matrix; Step 3: Design hopping beam patterns based on pseudo-random codes to obtain the final result of time slot resource allocation; the specific process is as follows: A skip beam pattern is a collection of ground-lit cells in a time slot; Due to onboard payload limitations, each time slot can only cover a maximum of K cells, and the sum of the beams illuminated in each time slot must be less than the maximum number of beams that the satellite can provide: In the formula, N is the number of ground cells and K is the number of beams; The beam lighting result for the nth cell in the tth time slot; The number of time slots per window; In the formula, Let be the beam illumination vector of all cells under the single-satellite coverage in time slot t. The dimension of the beam illumination vector is equal to the number of ground cells. make Satisfy the following formula: In the formula, the matrix The neighbor matrix represents the wavelet design, where adjacent cells are set to 1 and non-adjacent cells are set to 0. for Transpose of; The above equation will be satisfied Composition of pattern set In each time slot, a pattern is selected from Y, and the number of times each pattern is lit is defined as follows: The number of times the light is lit is a natural number. Since only one pattern is selected for each time slot, the sum of the number of times the light is lit is the number of time slots in the window. The number of times the Mth pattern is lit; The objective function is to maximize the minimum value of cell satisfaction, which is defined as the ratio of the communication capacity provided by the satellite to the communication capacity demand of the cell. The beam skipping problem is modeled as a convex optimization problem and solved using simulation software. In the formula, Let be the objective function. For constraint 1, For constraint condition 2, For constraint 3, For constraint 4, The throughput provided by the satellite to the nth cell. Let n be the communication capacity requirement of the nth cell. For natural numbers, For matrix The element in the m-th row and n-th column, The total number of communities The total number of patterns For question 1; The final result of system resource allocation is obtained based on the number of times each pattern is lit. ; A hopping beam pattern is defined within a hopping beam window length. The hopping beam pattern defines the set of cells illuminated in each time slot and is also considered the final result of system resource allocation.

2. The method for designing low-Earth orbit satellite hopping beam patterns based on precoding according to claim 1, characterized in that: The downlink precoding matrix is ​​obtained in step one; the specific process is as follows: Step 11: Model the channel matrix of the low-Earth orbit satellite downlink MIMO link; Steps 1 and 2: Obtain the downlink precoding matrix based on the channel matrix.

3. The method for designing low-Earth orbit satellite hopping beam patterns based on precoding according to claim 2, characterized in that: In step one, the channel matrix of the low-Earth orbit satellite downlink MIMO link is modeled: In the formula, The receiver antenna gain is expressed in W. The distance from the satellite to the k-th ground cell. For noise power, The noise temperature of the receiver. Let be the gain from the p-th antenna on the satellite to the k-th ground cell. Channel matrix The element in the k-th row and p-th column represents the channel factor from the p-th antenna on the LEO satellite to the k-th ground cell; Boltzmann's constant is expressed in joules per kelvin.

4. The method for designing low-Earth orbit satellite hopping beam patterns based on precoding according to claim 3, characterized in that: In steps one and two, the downlink precoding matrix is ​​obtained based on the channel matrix; the specific process is as follows: Give the expression for the received signal at the receiver end. : In the formula, This is the satellite transmission signal vector. It is Gaussian white noise. For the channel matrix, This is the precoding matrix; The precoding matrix The solution process is as follows: Precoding matrix based on the minimum mean square error criterion To minimize mean square error The optimal solution to the problem is to model the optimization problem and give constraints: In the formula, P is the total available power limit on the satellite, H is the conjugate transpose, and trace is the trace of the matrix; Thus, the expression for the precoding matrix based on the minimum mean square error (MMSE) is obtained: In the formula, It is the identity matrix. This represents the total number of beams.

5. The method for designing low-Earth orbit satellite hopping beam patterns based on precoding according to claim 4, characterized in that: In step two, the signal-to-interference-plus-noise ratio (SINR) and capacity are calculated based on the precoding matrix and the channel matrix; the specific process is as follows: set up and Channel matrix The q-th row and the precoding matrix The q-th column, where t represents the t-th time slot: In the formula, Let be the downlink signal-to-interference-plus-noise ratio of the q-th beam in the t-th time slot. For the precoding matrix The j-th column; The capacity of the nth ground cell corresponding to the qth beam is obtained based on the signal-to-interference-plus-noise ratio (SINR). In the formula, Let be the capacity of the nth cell in the tth time slot. Link bandwidth is measured in Hertz. The beam lighting result for the nth cell in the tth time slot; Capacity and beam hopping time slots Multiplying these together gives the throughput of each cell within time slot t: In the formula, N is the number of time slots for each window; N is the total number of cells.

6. The method for designing low-Earth orbit satellite hopping beam patterns based on precoding according to claim 5, characterized in that: In step three, the time slot resource allocation is a hopping beam that allocates different amounts of time resources to different beam positions, which is equivalent to the beam jumping to different coverage locations. Beam-skipping time window is defined as the length of time a region is stared at, defined as... ; A hopping beam slot is the smallest unit for allocating time resources to different beam positions, defined as follows: ; This gives the number of time slots for each window. : 。

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