Satellite Resource Deployment Optimizer for Dynamic NGSO Capacity

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Solution Overview

Problem

Existing resource optimization techniques fail to effectively manage the dynamic and fluctuating demands of non-geostationary satellite networks serving a large number of both stationary and mobile users, particularly in terms of allocating satellite and ground-based resources to maximize system capacity and revenue while adhering to constraints such as radiated power limits and frequency reuse.

Innovation Solution

The Resource Deployment Optimizer system employs linear programming and simulation techniques to determine quasi-optimal resource allocation, utilizing the Constellation Linearizer for interference protection and the Allocation Optimizer for efficient assignment of satellite and ground resources, along with the Demand Relaxation Algorithm to condition demands and the Fading Analysis and Mitigation function to optimize resource allocation under varying conditions.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If traditional resource allocation methods are used in NGSO satellite networks, then system simplicity is maintained, but resource allocation efficiency and system capacity deteriorate due to inability to handle dynamic demands

Engineering Contradiction:

Improveresource allocation efficiencyVSAvoidsystem complexity

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The patent implements dynamic resource allocation by continuously adjusting satellite beam assignments, frequency allocations, and power distribution based on real-time channel conditions, user mobility, and demand fluctuations. The system transitions from static to dynamic resource management to handle the highly mobile and time-varying nature of NGSO networks.

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The patent employs feedback mechanisms where channel state information, user location data, and quality of service metrics are continuously monitored and fed back to the resource allocation controller. This feedback enables adaptive adjustment of resource allocation decisions to optimize system performance under changing conditions.

Inventive Principle:

Principle #23Feedback

2Quantity of substance

If satellite resources are allocated to serve more users, then system capacity increases, but interference management becomes more difficult and frequency reuse constraints are violated

Engineering Contradiction:

Improvesystem capacityVSAvoidinterference

Core Design Contradiction:

Quantity of substanceVSObject-affected harmful factors

Solution Approach 1:

The patent applies frequency reuse by assigning different frequency sets to different spatial regions or user groups. Beams serving different geographic areas or user clusters can reuse the same frequencies when spatial separation ensures interference remains below acceptable thresholds, thereby increasing overall system capacity.

Inventive Principle:

Principle #3Local quality

Solution Approach 2:

The patent dynamically adjusts transmission power levels, beamforming weights, and frequency assignments based on channel conditions and interference measurements. By changing these parameters adaptively, the system maximizes capacity while maintaining interference within acceptable limits through real-time optimization.

Inventive Principle:

Principle #35Parameter changes

3Reliability

If handoff procedures are implemented for mobile users, then service continuity is maintained, but system complexity and resource management difficulty increase

Engineering Contradiction:

Improveservice continuityVSAvoidresource management complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The patent implements proactive handoff management by predicting user mobility trajectories and pre-establishing resource allocations for upcoming handoff points. The system prepares target satellite assignments and frequency allocations in advance based on predicted user movement, reducing handoff latency and complexity.

Inventive Principle:

Principle #10Preliminary action

4Productivity

If frequency reuse is implemented to increase capacity, then spectral efficiency improves, but interference management and frequency coordination become more complex

Engineering Contradiction:

Improvespectral efficiencyVSAvoidfrequency coordination complexity

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The patent implements frequency reuse by assigning different frequency sets to different spatial regions or user groups. Beams serving different geographic areas or user clusters can reuse the same frequencies when spatial separation ensures interference remains below acceptable thresholds, thereby increasing overall system capacity.

Inventive Principle:

Principle #3Local quality

Data Source

PatentUS11996928B2Resource deployment optimizer for non-geostationary and/or geostationary communications satellites

Publication Date: 2024.05.28 TELESAT LEO ULC

AI summary

Systems, methods and techniques are presented for discovering optimal solutions to satisfy communication traffic demands to a NGSO and GSO satellite constellations used for telecommunication. When multiple ground demands (mobile and stationary) are present, a satellite constellation requires an assignment of satellite resources to optimally match the ground demands. The systems, methods and techniques presented can utilize an optimization structure to maximize the objective function, using linear programming in combination with simulation and predictive features. The techniques presented determine optimal or quasi-optimal allocation of scarce and highly constrained satellite resources in an efficient manner. These techniques take into account maximizing capacity while protecting other geostationary and non-geostationary networks.