Evolutionary Game Multi-User Switching in Software-Defined Satellite Networks
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Solution Overview
Problem
Conventional satellite handover strategies in software-defined satellite networks fail to accurately indicate satellite load, leading to potential overloading and handover failures, as they rely on the number of idle channels and do not consider dynamic resource competition or user fairness.
Innovation Solution
A multi-user handover method based on evolutionary game theory, where user terminals calculate and compare revenue functions considering bandwidth allocation, remaining coverage time, and elevation angles to select a handover satellite, ensuring load balancing and fairness through a dynamic strategy adjustment process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If conventional satellite handover strategy selects satellite based on number of idle channels, then satellite load indication is simple, but satellite may be overloaded due to non-linear relationship between elevation angle and signal loss
Solution Approach 1:
The patent transforms the satellite load indication from a single parameter (number of idle channels) to a composite metric incorporating multiple parameters: number of idle channels, elevation angle, and remaining coverage time. This parameter transformation resolves the contradiction by maintaining computational simplicity while achieving accurate load indication through weighted combination of multiple factors.
Solution Approach 2:
The patent adds temporal dimension (remaining coverage time) and angular dimension (elevation angle) to the traditional load indication metric. This dimensional expansion allows the system to predict future load conditions and account for signal quality, resolving the inadequacy of static channel-count-based indication.
2Ease of operation
If all user terminals select satellite with least load based on idle channels, then each terminal maximizes its own benefit, but satellite becomes overloaded due to lack of coordination
Solution Approach 1:
The patent implements feedback mechanism where satellites broadcast their composite load metrics (incorporating idle channels, elevation angle, and remaining coverage time) to all user terminals. Terminals use this feedback to make informed handover decisions, balancing individual benefit maximization with system-wide load distribution. The feedback loop prevents overload by making overloaded satellites visible to terminals seeking handover targets.
Solution Approach 2:
The patent introduces a ground control station as intermediary that coordinates handover decisions. The ground control station receives handover requests from terminals, calculates optimal handover targets considering overall system load balance, and directs terminals to appropriate satellites. This intermediary resolves the conflict between autonomous terminal selection and system-wide load balancing.
3Duration of action of stationary object
If handover is performed frequently due to satellite movement, then continuous communication is maintained, but handover failure rate increases
Solution Approach 1:
The patent performs preliminary evaluation of candidate satellites before handover execution by computing composite metrics including remaining coverage time and elevation angle. Terminals pre-identify suitable handover targets and prepare handover requests in advance, reducing the risk of handover failures during actual handover execution. This preliminary action allows terminals to avoid satellites that will soon become unsuitable handover targets.
Solution Approach 2:
The patent incorporates remaining coverage time into the satellite selection metric as a cushioning factor. By preferring satellites with longer remaining coverage periods, the system builds a time buffer that reduces the frequency of subsequent handovers and minimizes handover failure risks. This beforehand cushioning accounts for the dynamic nature of satellite- terminal geometry and prepares for future handover needs.
Data Source
AI summary
The present application relates to the technical field of mobile communications, and specifically relates to an evolutionary game-based multi-user switching method in a software-defined satellite network system. The multi-user switching method comprises: respectively calculating the elevation angle and the remaining coverage time of a satellite according to obtained information, and calculating the payoff according to three basic factors, i.e., the capacity, the elevation angle, and the remaining coverage time of the satellite; a controller calculating the average payoff of users in the area, and broadcasting same to the users; when it is determined that the payoff of all the users is greater than the average payoff, ending multi-user switching; and when it is determined that the payoff of all the users is not greater than the average payoff, the users selecting other switching satellites having higher payoffs.