Satellite Communication Window Determination Using Graph Optimization
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Solution Overview
Problem
Existing technologies face challenges in efficiently determining communication access windows for downlink and crosslink communications in satellite constellations, due to spatial and temporal dependencies, as well as limitations in satellite capabilities such as slew agility and memory resources.
Innovation Solution
The method generates a communication graph with various node types and uses a task graph to determine access windows for downlink and crosslink communications. This involves connecting backbone nodes, data collection nodes, downlink nodes, crosslink-transmit nodes, and crosslink-receive nodes, and solving a mixed integer linear program (MILP) to optimize communication schedules.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If communication access windows are determined using existing technologies, then communication operations can be performed, but the determination process is inefficient due to spatial and temporal dependencies and satellite capability limitations
Solution Approach 1:
The patent segments the communication determination process into discrete graph nodes representing different satellite states and communication opportunities. By dividing the continuous temporal and spatial problem into discrete graphical elements (nodes and edges), the system can efficiently process and optimize communication windows without being constrained by continuous computational complexity.
Solution Approach 2:
The patent transforms the temporal problem of determining communication windows into a spatial graphical representation. By mapping time-dependent communication opportunities onto a graph structure with nodes and edges, the system converts a temporal optimization problem into a spatial path-finding problem that can be solved more efficiently using graph algorithms.
2Reliability
If satellite constellations perform downlink and crosslink communications, then data management is achieved, but spatial and temporal dependencies create complexity in determining access windows
Solution Approach 1:
The patent creates a universal communication graph that can represent multiple types of communication operations (downlink and crosslink) using the same graphical framework. The graph structure universally models all satellite-to-satellite and satellite-to-ground communications, allowing a single optimization approach to handle diverse communication scenarios without requiring separate determination processes for each type.
Solution Approach 2:
The communication graph serves as an intermediary structure between satellite capabilities and communication operations. By introducing this graphical representation as a mediator, the patent decouples the complexity of spatial-temporal constraints from the actual communication determination, allowing algorithms to work with the simplified graph structure rather than directly processing complex satellite orbital mechanics.
3Productivity
If satellite capabilities such as slew agility and memory resources are considered, then communication scheduling is optimized, but the determination of access windows becomes more constrained
Solution Approach 1:
The patent incorporates satellite-specific capabilities (slew agility, memory resources) as local properties of individual nodes in the communication graph. Each node can have customized attributes reflecting the specific satellite's capabilities and constraints at that particular state, allowing the optimization to account for local variations in satellite performance without imposing uniform constraints across the entire constellation.
Solution Approach 2:
The communication graph is designed to be dynamic, with nodes and edges that can be added or removed based on changing satellite capabilities and orbital positions. As satellites move and their capabilities change, the graph structure adapts by updating node properties and edge connections, maintaining flexibility while incorporating real-time capability constraints into the optimization process.
Data Source
AI summary
For determining a communication window is disclosed, a method generates a communication graph that includes backbone nodes, dummy nodes, data collection nodes, downlink nodes, crosslink send nodes, and crosslink receive nodes. The backbone nodes, the data collection nodes, the downlink nodes, the crosslink-transmit nodes, and the crosslink-receive nodes are connected by one of a homogenous edge between nodes of a same type and transition edges between nodes of a different type. The method determines access windows for downlink communications and crosslink communications using the communication graph. The method selects access windows based on a task graph generated from the communication graph. The method communicates from a given satellite within the selected access windows.


