Adaptive Satellite Network Closed-Loop Feedback
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Solution Overview
Problem
Current satellite network configurations are manually adjusted, leading to inefficiencies and a lack of self-optimization, as they do not incorporate closed-loop feedback, making them tedious, time-consuming, and unable to adapt dynamically to changing user demands or environmental conditions.
Innovation Solution
An adaptive self-optimizing network system using closed-loop feedback, where a global network operations center generates policies based on operator inputs and key performance indicators, transmitting configuration commands to satellites and receiving telemetry, allowing for real-time dynamic adjustments and self-optimization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If manual configuration changes are used for satellite networks, then operator control and flexibility are maintained, but the process becomes tedious, time-consuming, and lacks self-optimization capability
Solution Approach 1:
The patent implements closed-loop feedback by having the satellite system transmit performance data and operational status back to the ground station, which automatically analyzes this feedback and generates configuration adjustments. This creates a continuous cycle of monitoring, analysis, and optimization that eliminates manual intervention while maintaining adaptive control capability.
Solution Approach 2:
The satellite network is empowered with self-service capabilities through autonomous decision-making algorithms that can independently analyze performance data, identify optimization opportunities, and reconfigure payload elements without human intervention. The system serves itself by automatically detecting configuration needs and implementing changes based on real-time operational conditions.
2Adaptability or versatility
If manual configuration changes are implemented, then system stability is maintained through human oversight, but adaptability to changing user demands and environmental conditions deteriorates
Solution Approach 1:
The patent introduces dynamic reconfiguration capabilities where the satellite payload can automatically adjust its configuration in real-time based on changing operational conditions. The system transitions from static manual configuration to dynamic autonomous adaptation, allowing continuous optimization of beam forming, frequency allocation, and resource distribution according to real-time demand patterns and environmental factors.
Solution Approach 2:
The ground station pre-configures multiple payload configurations and performance thresholds before deployment. When operational conditions change, the satellite system can quickly switch between pre-planned configurations or generate new ones based on stored optimization algorithms, enabling rapid adaptation without time-consuming manual reconfiguration processes.
3Productivity
If automated closed-loop feedback systems are implemented, then self-optimization and dynamic adaptation improve, but system complexity increases
Solution Approach 1:
The patent divides the satellite payload into independently controllable elements or modules that can be individually reconfigured. This segmentation allows the complex optimization problem to be broken down into smaller, manageable sub-problems, where each module can be adjusted independently based on specific performance metrics, reducing the overall computational complexity while maintaining high productivity.
Solution Approach 2:
The ground station serves as an intermediary that hosts the complex optimization algorithms and decision-making logic, while the satellite itself executes relatively simple configuration changes. This distribution of computational complexity to the ground-based intermediary system allows the satellite to achieve sophisticated self-optimization without carrying heavy processing loads, thereby managing system complexity effectively.
Data Source
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AI summary
Systems, methods, and apparatus for an adaptive self-optimizing network using closed-loop feedback are disclosed. A method for sharing network resources comprises receiving (602), by a network operations center (NOC) (430), user demand for users (479) from an external network (471). The method further comprises receiving (630), by the NOC (430), key performance indicators from at least one internal network (470a, 470b). Also, the method comprises determining (640), by the NOC (430), whether at least one internal network (470a, 470b) has available resources by analyzing the key performance indicators and the user demand. Further, the method comprises allowing (650), by the NOC (430) when the NOC (430) determines that there are available resources, at least some of the users (479) from the external network (471) to connect to at least one internal network (470a, 470b) according to the available resources.