Satellite End Station Grouping for Lower Reporting Collisions
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Solution Overview
Problem
In conventional satellite communication systems, end stations are randomly grouped, leading to high collision probability and large system scheduling delay due to contention within end station groups when reporting control information, which affects communication quality.
Innovation Solution
A method for grouping end stations based on control information parameters, using metric values to balance the reporting status of each station, reducing collision probability by allocating end stations into groups with balanced metric values.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If end stations are randomly grouped, then the grouping process is simple, but the collision probability of control information is high
Solution Approach 1:
The patent changes the grouping parameter from random assignment to metric-based assignment. Each end station is assigned a metric value based on its control information reporting probability, and groups are formed by balancing these metric values. This parameter change reduces collision probability while maintaining manageable complexity through automated metric calculation and group formation algorithms.
2Device complexity
If end stations are randomly grouped, then the system complexity is low, but the system scheduling delay is large
Solution Approach 1:
The patent applies preliminary action by pre-calculating metric values for each end station based on their control information reporting probabilities before grouping. This allows the system to proactively balance the workload across groups, preventing future scheduling delays. The metric values are computed in advance using historical or estimated reporting probabilities, enabling optimized group formation without real-time complexity.
3Productivity
If end stations are grouped to reduce contention, then the reporting capacity should increase, but the collision probability remains high due to random allocation
Solution Approach 1:
The patent applies local quality by assigning different metric values to different end stations based on their individual control information reporting probabilities. Instead of uniform random grouping, each station is evaluated locally and placed in groups where its metric value balances with other members. This local differentiation ensures that groups with higher reporting probabilities are better distributed, reducing collisions while maximizing reporting capacity.
Data Source
AI summary
A method for grouping end stations in a satellite system, a controller, a satellite system, and a computer storage medium are disclosed. The method may include: acquiring a control information parameter of each of a plurality of end stations, where the control information parameter includes a control information reporting probability; obtaining a metric value of each of the plurality of end stations according to the control information parameter; obtaining an upper limit metric value according to the metric values of the plurality of end stations and a preset group number N; and grouping the plurality of end stations according to a preset grouping principle and the upper limit metric value to obtain N end station groups.


