A low-orbit satellite communication network persistent routing planning method based on MILP

Abstract

This invention discloses a persistent routing planning method for low-Earth orbit (LEO) satellite communication networks based on mixed-integer linear programming (MILP), belonging to the technical field of LEO satellite network routing planning. The method includes the following steps: Step 1: Define the parameter representation of LEO satellite communication network attribute data, including network nodes, communication link contact windows, etc.; Step 2: Establish a persistent routing planning (MILP) model for LEO satellite communication networks based on communication link contact windows and feasible flow theory, characterizing the end-to-end persistent communication process of communication links through a network flow model; Step 3: Solve the model using a branch-and-bound algorithm to obtain the precise optimal link configuration that maximizes the end-to-end communication duration. This invention overcomes the limitation of heuristic algorithms in terms of solution quality evaluation, providing a reliable persistent routing planning tool for LEO satellite networks and improving the theoretical completeness and engineering applicability of persistent data routing strategies in the highly dynamic environment of low Earth orbit.

Description

Technical Field

[0001] This invention relates to the field of routing planning technology for low-Earth orbit satellite networks, and specifically to a continuous routing planning method for low-Earth orbit satellite communication networks based on MILP. Background Technology

[0002] In building a next-generation cross-domain integrated information network with global coverage, high bandwidth, and low latency, low-Earth orbit (LEO) satellite constellations, as the core architecture of the space domain network, directly determine the effectiveness of space-based communication services through their continuous routing. LEO satellite networks need to seek persistent end-to-end connectivity under multiple spatiotemporal constraints, including high-speed satellite movement, periodic interruptions in inter-satellite links, and limited satellite-to-ground windows, to support critical services such as remote sensing data backhaul, emergency real-time command and control, and global intelligent interconnection.

[0003] Existing routing methods for low-Earth orbit (LEO) satellite networks generally employ rule-based heuristics, such as deep reinforcement learning and genetic programming. While these methods are computationally efficient, they often fail to fully capture the global spatiotemporal characteristics of the network, easily getting trapped in local optima. This results in insufficient end-to-end persistence of the generated routes, making it difficult to meet service continuity requirements. Therefore, there is an urgent need for a planning method that can efficiently identify the most persistent end-to-end communication routes in LEO satellite networks. Summary of the Invention

[0004] To address the aforementioned issues, this invention proposes a persistent routing planning method for low-Earth orbit (LEO) satellite communication networks based on MILP (Multi-Input Multiple-Output) theory. A MILP model for persistent routing planning in LEO satellite communication networks is constructed based on the communication link contact window and feasible flow theory. By accurately characterizing link availability and traffic continuity, the optimal routing link configuration that maximizes end-to-end communication duration is obtained. This provides a reliable and accurate solution for persistent routing planning in LEO satellite networks, improving the theoretical completeness and engineering applicability of persistent data routing strategies in the highly dynamic environment of near-Earth orbit.

[0005] A continuous route planning method for low-Earth orbit satellite communication networks based on MILP includes the following steps:

[0006] Step 1: Define the parameter representation of low-Earth orbit satellite communication network attribute data;

[0007] Specifically: Let N be the set of nodes that make up the low-Earth orbit satellite communication network, i be the index of the node and i = 1, 2, ..., |N|, where the ground terminal source point is O, the ground terminal sink point is D, the set of communication links between any pair of nodes is L, (i, j) is the index of the communication link, and the set of contact time windows of communication link (i, j) is W. ij w is the index of the contact time window and w = 1, 2, …, |W ijThe start time of the w-th contact time window of the communication link (i, j) is ls. ijw The termination time of the w-th contact time window of the communication link (i, j) is le ijw M is a large number, such as 9999.

[0008] Step 2: Establish a continuous routing planning (MILP) model for low-Earth orbit (LEO) satellite communication networks based on the communication link contact window and feasible flow theory. The spatiotemporal link configuration of end-to-end continuous routing in the LEO satellite network is used as the decision variable, and maximizing the communication duration is the optimization objective. The specific method is as follows:

[0009] Step 2.1: Define the decision variables for routing planning of low-Earth orbit satellite communication networks;

[0010] x ijwp : A variable of 0 or 1, which is 1 if and only if the communication link (i, j) is used to construct the maximum persistent path in its w-th contact time window, and 0 otherwise;

[0011] CE: Start time of the maximum persistent path;

[0012] CS: End time of the maximum persistent path;

[0013] Step 2.2: Establish the objective function for continuous routing planning of low-Earth orbit satellite communication networks;

[0014] (1)

[0015] Wherein, objective function Indicates the duration of the maximum persistent path;

[0016] Step 2.3: Establish a formalized representation of the end-to-end communication process based on link contact windows and feasible network flows;

[0017] (2)

[0018] (3)

[0019] (4)

[0020] (5)

[0021] (6)

[0022] Step 2.4: Calculate the start and end times of the maximum persistent path;

[0023] (7)

[0024] (8)

[0025] (9)

[0026] (10)

[0027] Step 2.5: Variable value constraints;

[0028] (11)

[0029] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0030] This invention overcomes the limitation of heuristic methods that can only obtain local optimal solutions by introducing a modeling framework based on link contact window and feasible flow theory. It constructs a solvable persistent routing planning (MILP) model for low-Earth orbit satellite communication networks at the spatiotemporal global level, forming an accurate link-optimal configuration that maximizes end-to-end communication duration. Through proactive planning, it effectively avoids path interruption problems caused by insufficient spatiotemporal search, and improves the theoretical completeness and engineering applicability of persistent data routing strategies in the highly dynamic environment of low-Earth orbit. Attached Figure Description Figure 1 This is a flowchart of a continuous routing planning method for low-Earth orbit satellite communication networks based on MILP, as described in this invention. Figure 2 This is a schematic diagram of the link configuration for the longest end-to-end persistent route in a low-Earth orbit satellite network. Detailed Implementation

[0031] The present invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0032] A continuous route planning method for low-Earth orbit satellite communication networks based on MILP includes the following steps:

[0033] Step 1: Define the parameter representation of low-Earth orbit satellite communication network attribute data;

[0034] Specifically: Let N be the set of nodes that make up the low-Earth orbit satellite communication network, i be the index of the node and i = 1, 2, ..., |N|, where the ground terminal source point is O, the ground terminal sink point is D, the set of communication links between any pair of nodes is L, (i, j) is the index of the communication link, and the set of contact time windows of communication link (i, j) is W. ij w is the index of the contact time window and w = 1, 2, …, |W ij The start time of the w-th contact time window of the communication link (i, j) is ls. ijw The termination time of the w-th contact time window of the communication link (i, j) is le ijwM is a large number, such as 9999.

[0035] Step 2: Establish a MILP model for continuous routing planning of low-Earth orbit satellite communication networks based on feasible flow theory. The spatiotemporal link configuration of end-to-end continuous routing of low-Earth orbit satellite networks is used as the decision variable, and maximizing the communication duration is the optimization objective. The specific method is as follows:

[0036] Step 2.1: Define the decision variables for routing planning of low-Earth orbit satellite communication networks;

[0037] x ijwp : A variable of 0 or 1, which is 1 if and only if the communication link (i, j) is used to construct the maximum persistent path in its w-th contact time window, and 0 otherwise;

[0038] CE: Start time of the maximum persistent path;

[0039] CS: End time of the maximum persistent path;

[0040] Step 2.2: Establish the objective function for continuous routing planning of low-Earth orbit satellite communication networks;

[0041] (12)

[0042] Wherein, objective function Indicates the duration of the maximum persistent path;

[0043] Step 2.3: Establish a formalized representation of the end-to-end communication process based on the network flow method;

[0044] (13)

[0045] (14)

[0046] (15)

[0047] (16)

[0048] (17)

[0049] Step 2.4: Calculate the start and end times of the maximum persistent path;

[0050] (18)

[0051] (19)

[0052] (20)

[0053] (twenty one)

[0054] Step 2.5: Variable value constraints;

[0055] (twenty two)

[0056] Step 3: Solve the MILP model for continuous routing planning of low-Earth orbit satellite communication networks to obtain the optimal routing link configuration that maximizes the end-to-end communication duration.

[0057] This implementation uses the branch and bound algorithm embedded in the commercial MILP solver CPLEX 12.9.0 on the GNU / Linux 4.15.0-142-generic x86_64 operating system to solve the model;

[0058] To demonstrate the superiority of the method proposed in this invention, this embodiment names the MILP model constructed by this invention as Continuous Routing Planning Model 1, or simply Model 1, and the routing model constructed based on reinforcement learning as Heuristic Routing Model 2, or simply Model 2.

[0059] To facilitate the representation of model results, this embodiment introduces several symbols to represent the results of each model: the end-to-end continuous communication duration obtained by the model is represented by Dur, and the corresponding computation time is represented by CT;

[0060] To facilitate the quantification of model differences, this embodiment introduces the difference in end-to-end continuous communication duration between indicator nodes, using D. Dur The calculation formula is shown below:

[0061] (twenty three)

[0062] The CAS100ATA ground station was selected as the end-to-end communication source node, the WDC500USA ground station was selected as the destination node, the orbital data of the Iridium-NEXT constellation of 80 low-orbit satellites on July 10, 2025 were selected to construct the communication link and contact time window set, and all satellites and ground nodes were selected to construct the network node set. The value of M is 9999.

[0063] The experimental results are shown in Table 1. In terms of solution efficiency, both routing models can obtain the optimal solution within seconds for all test instances. Regarding the objective function, Model 2, compared to Model 1, achieves the optimal end-to-end communication time through global link configuration planning, with an average duration of 232.33 seconds and an average D... Dur Reaching 14.09%;

[0064] Table 1 Comparison of results between the two models

[0065]

[0066] The comparison results above show that the MILP-based persistent routing planning method for low-Earth orbit satellite communication networks designed in this invention exhibits global optimality in terms of end-to-end communication duration. It overcomes the limitation that the solution quality of heuristic algorithms cannot be evaluated, provides a reliable and accurate solution for the optimal routing link configuration for persistent routing planning of low-Earth orbit satellite networks, and improves the theoretical completeness and engineering applicability of persistent data routing strategies in the highly dynamic environment of near-Earth orbit.

Claims

1. A continuous route planning method for low-Earth orbit satellite communication networks based on MILP; comprising the following steps: (1) Define the parameter representation of attribute data for low-Earth orbit satellite communication networks; Let N be the set of nodes that make up the low-Earth orbit satellite communication network, and let i be the index of the node, where i = 1, 2, …, |N|. Let O be the source node of the ground terminal and D be the sink node of the ground terminal. Let L be the set of communication links that make up any pair of nodes, and let (i, j) be the index of the communication link. Let W be the set of contact time windows that make up the communication link (i, j). ij w is the index of the contact time window and w = 1, 2, …, |W ij The start time of the w-th contact time window of the communication link (i, j) is ls. ijw The termination time of the w-th contact time window of the communication link (i, j) is le ijw M is a large number, such as 9999; (2) Establish a continuous routing planning (MILP) model for low-Earth orbit (LEO) satellite communication networks based on communication link contact window and feasible flow theory. The link configuration for end-to-end continuous routing in the LEO satellite network is used as the decision variable, and maximizing communication duration is the optimization objective. The specific method is as follows: (2.1) Define the decision variables for routing planning in low-Earth orbit satellite communication networks; define variable CE to represent the start time of the maximum persistent path; define variable CS to represent the end time of the maximum persistent path; define variable x ijwp The variable represents a 0 or 1, which is 1 if and only if the communication link (i, j) is used to construct the maximum persistent path in its w-th contact time window, and 0 otherwise; (2.2) Establish the objective function for continuous routing planning of low-Earth orbit satellite communication networks: (2.3) Establish a formalized representation of the end-to-end communication process based on link contact windows and feasible network flows: (2.4) Calculate the start and end times of the maximum persistent path: (2.5) Variable value constraints: (3) The MILP model of persistent routing planning for low-Earth orbit satellite communication network is solved by the branch and bound algorithm, and a reliable and accurate solution of the optimal routing link configuration that maximizes the end-to-end duration is obtained. This breaks through the limitation that the solution quality of heuristic algorithms cannot be evaluated, and improves the theoretical completeness and engineering applicability of persistent routing strategy for data in the high dynamic environment of low Earth orbit.

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