A satellite switching method based on prediction feedback

Abstract

The present invention relates to a satellite switching method based on prediction feedback, which belongs to the field of satellite communication technology, and includes the following steps: the satellite side establishes a satellite-to-ground connection binary; the user side predicts the mobile trajectory, and reports the pre-switching information including the mobile behavior and communication demand of the user node within a future prediction time to the satellite; the satellite side builds a switching utility function including a satellite load balancing index and a user satisfaction index; the switching utility function is optimized using a multi-objective optimization algorithm, and each user side switches the satellite according to the obtained optimal solution; the prediction time length is dynamically adjusted according to error feedback, and the prediction is re-performed after adjustment. The present invention optimizes satellite switching decisions, reduces unnecessary switching, improves communication quality and stability, solves the problem of frequent switching or even disconnection of ground access terminals due to the high-speed movement of low-orbit satellites, and improves the service quality of ground terminals accessing satellite networks.

Description

Technical Field

[0001] The invention relates to the technical field of satellite communications, and in particular to a satellite switching method based on prediction feedback. Background Art

[0002] As an emerging communication technology, low-orbit satellite networks have broad application prospects and development potential. Compared with traditional ground communication networks, low-orbit satellite networks have the following advantages: wide-area coverage, low latency and flexible deployment. These advantages make low-orbit satellite networks an ideal choice for solving communication problems in areas with imperfect infrastructure, low population density or remote areas.

[0003] In remote areas, the construction and maintenance costs of traditional ground communication facilities are high, while low-orbit satellite networks can provide relatively economical and efficient communication services through their wide coverage and low signal transmission delay. Therefore, low-orbit satellite networks have important application value in providing emergency communications, rural communications, maritime communications, and emergency rescue.

[0004] However, due to the high-speed motion of low-orbit satellites, the duration of inter-satellite and satellite-to-ground links between satellites and users is limited, and the link status is easily affected by factors such as distance and pitch angle. This results in the need for terminals to frequently switch satellites during low-orbit satellite services to maintain communication connections. Frequent switching not only increases the system burden, but may also cause link interruption problems, affecting user communication quality and experience.

[0005] There are roughly three types of low-orbit satellite switching. One is intra-satellite switching, which refers to the user's switching between beams in a multi-beam satellite. The solution for point beam switching is relatively mature. The second is inter-satellite link switching, which refers to the switching caused by unstable links during rapid movement between satellites. However, due to the small number of satellites at present, there is relatively little research on this issue. The third is inter-satellite switching. Since a single satellite moves at a fast speed and is visible to ground users for only about 10 minutes, in order to maintain the stability of the call, the mobile terminal needs to disconnect from the current satellite and connect to another new satellite. The connection relationship between the satellite and the terminal needs to be constantly changed. Inter-satellite switching technology has not yet matured and is still a focus of academia and industry.

[0006] In recent years, existing solutions to the multi-node switching problem still have some defects. The traditional low-orbit satellite switching solution uses signal thresholds to trigger switching, but due to signaling transmission delays, the user switching time is long, resulting in poor user experience. At the same time, with a wide coverage area and a large user base, too many switching users will cause the low-orbit satellite access of the switching target to be overloaded, affecting link stability.

[0007] Researchers have proposed group switching and conditional switching solutions to optimize the switching process of low-orbit satellites. Group switching reduces the switching load by grouping users within the coverage area and initiating switching commands within the same group, but it causes synchronization problems. Conditional switching sets the switching conditions in advance and automatically triggers the switching to solve the problem of instantaneous switching users. However, the selection of conditions is critical, and switching needs to be done at the right time to avoid frequent switching.

[0008] Although group switching and conditional switching have optimized the switching load to a certain extent, they still face complexity and multi-satellite selection problems. Group switching increases system complexity, which is especially challenging in scenarios with wide coverage and high user density. Conditional switching requires reasonable selection of switching conditions to ensure switching accuracy. However, a better solution has not yet been found for the switching problem of multi-satellite selection, which may cause redundant switching for users, affecting communication efficiency and stability. Summary of the invention

[0009] In order to overcome the problems of frequent switching and link interruption of low-orbit satellites and the existing multi-satellite selection switching that may cause redundant switching of users, affecting communication efficiency and stability, the present invention proposes a satellite switching method based on predictive feedback. The method predicts the user's movement trajectory and communication needs, optimizes satellite switching decisions, reduces unnecessary switching, and improves communication quality and stability, thereby solving the problem of frequent switching or even disconnection of ground access terminals due to the high-speed movement of low-orbit satellites in low-orbit satellite networks, improving the service quality of ground terminals accessing satellite networks, and further expanding the application areas and user satisfaction of low-orbit satellite networks.

[0010] To achieve the above object, the present invention adopts the following technical solutions:

[0011] A satellite switching method based on prediction feedback comprises the following steps:

[0012] Step 1: The satellite side establishes a satellite-to-ground connection binary;

[0013] Step 2: Each user side predicts its own movement trajectory and reports the predicted pre-switching information to the satellite. The pre-switching information includes the movement behavior and communication needs of the user node within a predicted period of time in the future.

[0014] Step 3: The satellite side builds a switching utility function, which includes a satellite load balancing index and a user satisfaction index;

[0015] Step 4: Optimize the switching utility function using a multi-objective optimization algorithm to obtain an optimal satellite switching solution, and each user side switches the connected satellite according to the optimal satellite switching solution;

[0016] Step 5: Dynamically adjust the prediction time length according to the error feedback between trajectory prediction and communication demand prediction, and return to step 2 after adjustment.

[0017] The present invention aims to propose a low-orbit satellite switching method that comprehensively considers multiple angles such as satellite load, service time, and user experience. Through prediction technology and optimization algorithms, the switching efficiency and stability are improved to provide users with better and more reliable communication services. At the same time, the present invention is expected to provide new solutions and optimization directions for the further development and application of low-orbit satellite communication switching technology, further promote the development of low-orbit satellite communication technology, and provide more reliable and efficient solutions for communication problems in remote areas and special environments. The present invention has the following beneficial effects:

[0018] (1) Improving the communication quality and user experience of low-orbit satellite networks: By predicting and optimizing switching decisions, the present invention can reduce the number of unnecessary switching times and the probability of link interruption, thereby improving the communication quality and stability in low-orbit satellite networks; users can switch satellites more smoothly during movement and enjoy more continuous and stable communication services, significantly improving user experience;

[0019] (2) Optimizing handover decisions: The present invention comprehensively considers multiple factors such as satellite load, service time, and user experience, constructs a utility function, and uses the CRITIC algorithm to optimize the handover solution, which makes the handover decision more intelligent and comprehensive, ensures the best balance between multiple performance indicators, and improves the accuracy and effectiveness of the handover decision;

[0020] (3) Providing pre-switching information: By using Markov chain prediction technology, the present invention provides pre-switching information, including the user's future mobility behavior and communication needs. This prior knowledge provides more basis for the switching decision, making the switching more targeted and real-time, and effectively coping with the situation where the user moves quickly and the communication needs change rapidly;

[0021] (4) Reducing the switching call drop rate: The present invention reduces the number of times users switch satellites by optimizing the switching scheme and providing pre-switching information, effectively reducing the switching call drop rate; users no longer need to switch satellites frequently during the communication process, reducing the risk of communication interruption and disconnection, and improving the stability of the communication connection;

[0022] (5) Wide applicability: The technical solution of the present invention can be applied to various low-orbit satellite communication scenarios, including communications in remote areas, high-speed trains and aircraft, etc. Regardless of the scenario with wide coverage, high user density, or fast user movement speed, the technical solution can provide an effective switching solution;

[0023] (6) Promoting the development of low-orbit satellite communication technology: By optimizing switching decisions and improving communication quality, the present invention is expected to promote the development and application of low-orbit satellite communication technology; with the continuous improvement and optimization of technology, the low-orbit satellite communication system will be more stable and efficient, providing more reliable communication services for remote areas and high-speed mobile users. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 A scene graph to which the present invention is applicable;

[0025] Figure 2 A flowchart of a satellite switching method based on prediction feedback according to an embodiment of the present invention;

[0026] Figure 3 Bipartite graph for satellite users;

[0027] Figure 4 Schematic diagram of satellite coverage for user U0;

[0028] Figure 5 Prediction diagram for user communication needs. DETAILED DESCRIPTION

[0029] The technical solution of the present invention will be described in detail below in conjunction with the accompanying drawings and preferred embodiments.

[0030] The present invention is applicable to scenarios such as Figure 1 As shown, there are M low-orbit satellite network users, namely U1, U2, ..., U M , there are N low-orbit satellites, namely S1, S2, ..., S N , ground users are in a stationary or moving state and can be covered by multiple satellites at the same time. There are inter-satellite communication links between low-orbit satellites, which can exchange information. The present invention proposes a low-orbit satellite switching method that comprehensively considers multiple angles such as satellite load, service time, and user experience. The method improves switching efficiency and stability through prediction technology and optimization algorithms, and provides users with better quality and more reliable communication services.

[0031] Specifically, the satellite switching method based on prediction feedback proposed in the embodiment of the present invention includes the following steps 1 to 5, and the process is as follows: Figure 2 shown.

[0032] Step 1: The satellite side establishes a satellite-to-ground connection pair.

[0033] Based on the existing network topology and user location information, the low-orbit satellite establishes a model of the switching process. A bipartite graph is used to describe the satellite-node connection relationship, and the user and satellite nodes are represented as two types of nodes in the bipartite graph. This can intuitively represent the network status and facilitate the calculation of subsequent switching decisions. A(s,u) and C(s,u) are used to represent the connection set and coverage set respectively. The coverage and connection of the node can be fed back to the satellite network through the node. The satellite user bipartite graph is as follows Figure 3 As shown in Figure 1, it includes satellite sets and user sets. After determining the satellite-user bipartite graph, the corresponding satellite-ground connection tuple can be obtained.

[0034] Step 2: The user side calculates the pre-switching information.

[0035] Considering the poor computing power of the satellite side and the large number of user nodes, the unified prediction method is not realistic. Therefore, each user node is independently predicted and reported to the satellite. Each user side uses Markov chain to predict the movement trajectory of the terminal node, obtain pre-switching information and report it to the satellite. The pre-switching information includes the user's mobile behavior and communication needs in the future prediction time, which can provide prior knowledge for the switching decision, making the switching more targeted and timely. The total predictable time length is T, and the time is discretized for analysis. Through the user's mobile behavior and the low-orbit satellite orbit, the coverage relationship between the user and the satellite can be predicted for a period of time in the future. The prediction of communication needs mainly refers to the demand of the ground node for the channel bandwidth, which can provide help for the load of the low-orbit satellite. In addition to the Markov chain prediction technology, this step can also use other prediction models, such as neural networks, time series models, etc. to predict the user's movement trajectory and communication needs. Different prediction models may have better prediction performance in different scenarios, and the appropriate prediction model can be selected according to the actual situation.

[0036] After comprehensive analysis of mobile behavior and orbit, each user can get a satellite coverage diagram, such as Figure 4 The figure shows a schematic diagram of satellite coverage for user U0, where the horizontal axis is time t and the vertical axis is satellite ID. The shaded part indicates that the user is within the satellite coverage at the moment of shadow coverage, otherwise the user is not within the satellite coverage.

[0037] At the same time, after communication prediction, the communication demand prediction graph of each node can be obtained, such as Figure 5 As shown, the horizontal axis in the figure is time t, and the vertical axis is the user's channel bandwidth B w , t0 is the current time.

[0038] Step 3: Set up the switching utility function on the satellite side.

[0039] For the scenario of user multi-satellite switching selection, a switching utility function is constructed, which comprehensively considers satellite load conditions and user experience factors. The formula of the switching utility function is as follows:

[0040]

[0041] Among them, l n (t) is the load balancing function on the satellite side, r m (t) is the user satisfaction measurement function, ω is the weight coefficient, which is used to adjust the balance between satellite load and user satisfaction. T is the prediction time length. This utility function will serve as the basis for switching decisions and is used to evaluate the benefits and costs of users switching to different satellites.

[0042] Satellite side load balancing measurement function l n (t) Considering the satellite load, it mainly reflects the satellite channel load. The specific formula is as follows:

[0043]

[0044] Among them, B w (t) is the bandwidth used by the satellite at time t, B max is the maximum bandwidth of the satellite, δ is the satellite load factor, which can control the optimal target of satellite load, and σ controls B w (t) The degree of influence of the change. When σ is larger, it means that B w (t) changes have little effect on load performance, and when σ is large, the impact is greater.

[0045] r m (t) is the user satisfaction measurement function, which is mainly affected by channel quality and number of handovers. The specific formula is as follows:

[0046]

[0047] Among them, T is the total prediction time, that is, the prediction time length, M is the total number of users, and d m (t) is a binary variable of 0 or 1, which indicates whether the communication requirements of the satellite are met for user m at time t. m (t) is the total number of handovers of user m from time 0 to time t, and its initial value is 1. m (t) can well reflect the user satisfaction and comprehensively consider the satellite communication needs and the impact of the number of switching times.

[0048] When solving the low-orbit satellite switching problem, the key step of the present invention is to construct a utility function that comprehensively considers factors such as satellite load, service time, user experience, etc. The switching utility function proposed in this embodiment is the core basis for switching decisions, and a more accurate switching strategy is achieved by quantifying the importance and weights of multiple factors.

[0049] Furthermore, in addition to signal strength, load conditions, and transmission delay, the switching utility function can also include other performance indicators, such as energy consumption and bandwidth utilization, to more comprehensively evaluate the switching solution. The types and weights of performance indicators can be expanded according to specific application scenarios and requirements.

[0050] In addition to the handover utility function formula provided in this embodiment, different utility functions may be used to comprehensively consider factors such as satellite load, service time, user experience, etc. Different utility function forms may lead to different handover decision results, so different function forms may be tried to optimize the handover solution.

[0051] The present invention comprehensively considers the performance indicators of the user side and the satellite side in the switching decision, such as signal strength, load condition, transmission delay, etc., to ensure the comprehensive optimization of the switching decision on the user experience and network quality.

[0052] Step 4: Use a multi-objective optimization algorithm to optimize the switching utility function and solve the optimal satellite switching solution.

[0053] Based on the pre-switching information and the low-orbit satellite load, the user-side communication service quality and the low-orbit satellite channel load are comprehensively considered, and the CRITIC (Cross-Criteria Decision Making) algorithm can be used to solve the optimal switching solution. Specifically, the weight vector w is first initialized, and then the comprehensive switching utility function is calculated, while considering factors such as the satellite channel quality and the number of switching times. The weight vector is adjusted according to the change of the objective function value, so that it gradually approaches the optimal value, and repeated iterations make the switching utility function reach the maximum value or convergence, so as to balance the user-side communication service quality and the low-orbit satellite channel load in the switching decision, find the optimal satellite switching solution, and each user side switches the connected satellite according to the optimal satellite switching solution to improve the user service quality and reduce the satellite load, thereby optimizing the overall system performance. The CRITIC algorithm can effectively handle multi-objective optimization problems and ensure that the switching decision achieves the best balance under multiple factors. Through the comprehensive use of pre-switching information and the CRITIC algorithm, the present invention can optimize the switching solution, avoid unnecessary switching and reduce the switching drop rate, and further improve the user service quality and communication stability.

[0054] In addition to the CRITIC algorithm, the multi-objective optimization algorithm can also use other optimization algorithms to solve the optimal satellite switching solution, such as genetic algorithm, simulated annealing algorithm, etc. Different optimization algorithms may have better convergence and efficiency in different situations, and the algorithm can be improved or replaced.

[0055] At the same time, the present invention can also optimize the execution method of the switching strategy, such as appropriately adjusting the triggering conditions of the switching, the execution timing of the switching strategy, etc., to further improve the accuracy and real-time performance of the switching, and introduce machine learning technology to further optimize the switching decision and prediction model. Through machine learning, the user's behavior patterns and communication needs can be better explored, providing more accurate prediction information for the switching decision.

[0056] Step 5: Switching effect evaluation.

[0057] Considering the error between trajectory prediction and communication demand prediction, this step dynamically adjusts the prediction time length according to the error feedback between trajectory prediction and communication demand prediction after reaching time T, and optimizes the communication quality within an acceptable error range. Otherwise, the actual link and the imaginary link will be too far apart due to invalid prediction, which will cause the strategy to fail. After adjusting the prediction time length, return to step 2 and re-predict the mobile trajectory.

[0058] The satellite switching method of this embodiment can customize the technical solution for different application scenarios and usage scenarios. For example, in the high-speed train communication scenario, it can be optimized based on the characteristics of high-speed movement; in the remote area communication scenario, it can focus on factors such as satellite load and user density.

[0059] In summary, the key point of the present invention is to solve the user switching problem in the low-orbit satellite network by constructing utility functions, providing pre-switching information, and using the CRITIC algorithm to optimize the switching scheme and other innovative technologies, thereby improving communication quality, optimizing user experience, and bringing new breakthroughs and innovations to the development and application of low-orbit satellite communication technology. The advantages of the present invention are to improve communication quality and user experience, optimize switching decisions, provide pre-switching information, reduce the switching drop rate, and be applicable to various low-orbit satellite communication scenarios, bringing positive impacts to the development and application of low-orbit satellite communication technology.

[0060] The technical features of the above-described embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above-described embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0061] The above-mentioned embodiments only express several implementation methods of the present invention, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the concept of the present invention, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention shall be subject to the attached claims.

Claims

1. A satellite switching method based on prediction feedback, characterized in that: The following steps are involved: Step 1: The satellite side establishes a satellite-to-ground connection binary; Step 2: Each user side predicts its own movement trajectory and reports the predicted pre-switching information to the satellite. The pre-switching information includes the movement behavior and communication needs of the user node within a predicted period of time in the future. Step 3: The satellite side builds a switching utility function, which includes a satellite load balancing index and a user satisfaction index; the formula of the switching utility function is as follows: Among them, l n (t) is the load balancing function on the satellite side, r m (t) is the user satisfaction measurement function, ω is the weight coefficient used to adjust the balance between satellite load and user satisfaction, T is the prediction time length, M is the total number of users, and N is the total number of satellites; Satellite side load balancing measurement function l n The formula for (t) is as follows: Among them, B w (t) is the bandwidth used by the satellite at time t, B max is the maximum bandwidth of the satellite, δ is the satellite load factor, which can control the optimal target of satellite load, and σ controls B w (t) The degree of influence of the change. When σ is larger, it means that B w (t) changes have little effect on load performance, and when σ is small, the impact is greater; User satisfaction measurement function r m The formula for (t) is as follows: Among them, d m (t) is a binary variable of 0 or 1, which indicates whether the communication requirements of the satellite are met for user m at time t. m (t) is the total number of handovers of user m from time 0 to time t, with an initial value of 1; Step 4: Optimize the switching utility function using a multi-objective optimization algorithm to obtain an optimal satellite switching solution, and each user side switches the connected satellite according to the optimal satellite switching solution; Step 5: Dynamically adjust the prediction time length according to the error feedback between trajectory prediction and communication demand prediction, and return to step 2 after adjustment.

2. A satellite switching method based on prediction feedback according to claim 1, characterized in that: The mobility behavior of user nodes is represented by the satellite coverage diagram, and the communication demand is represented by the communication demand prediction diagram.

3. The satellite switching method based on prediction feedback according to claim 1, characterized in that: The user side uses any one of the Markov chain, neural network and time series models to predict the movement trajectory.

4. The satellite switching method based on prediction feedback according to claim 1, characterized in that: The multi-objective optimization algorithm is any one of a CRITIC algorithm, a genetic algorithm and a simulated annealing algorithm.

Images