Satellite Signal Detection via Hypothesis Pairing and Channel Selection
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Solution Overview
Problem
Existing communication systems, such as LTE-M and NB-IoT, fail to provide global scale and cost-effective connectivity for the Global Asset Tracking and Monitoring Market, particularly in terms of indoor penetration and connectivity costs.
Innovation Solution
The method involves correlating frames received from a satellite with multiple hypotheses to detect signal metrics, identifying subsets of hypotheses, and selecting channels for transmission based on these metrics, employing frequency diversity, power control schemes, and forward error correction to optimize communication links and reduce latency, power consumption, and operational costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If existing communication systems (LTE-M and NB-IoT) are used, then connectivity is provided, but global scale and cost-effective connectivity are not achieved
Solution Approach 1:
The patent implements a universal communication system that can operate with both satellite and terrestrial towers, allowing the same endpoint device to function globally without requiring different hardware or protocols for different regions. The system selects between satellite and tower based on availability, providing universal coverage across global asset tracking scenarios.
Solution Approach 2:
The system dynamically changes operational parameters by selecting different communication channels (satellite vs. tower) based on signal metrics, channel availability, and cost considerations. This parameter switching enables cost-effective connectivity by preferring lower-cost terrestrial towers when available while maintaining global coverage through satellite fallback.
2Object-affected harmful factors
If satellite communication is used for global coverage, then indoor penetration is improved, but connectivity cost increases
Solution Approach 1:
The communication system dynamically adapts its behavior by continuously monitoring channel conditions and signal metrics, switching between satellite and terrestrial tower modes based on real-time requirements. This dynamic approach ensures satellite communication (with better indoor penetration) is used only when necessary, while preferring cost-effective terrestrial towers during normal operations.
Solution Approach 2:
The system changes operational parameters by selecting different transmission channels based on indoor/outdoor environment detection, signal strength metrics, and cost considerations. When indoor penetration is required and satellite signal is available, the system switches to satellite mode; otherwise, it uses terrestrial towers to minimize costs.
3Measurement precision
If multiple hypotheses are correlated for each frame, then detection accuracy is improved, but processing complexity increases
Solution Approach 1:
The patent applies partial action by correlating frames with multiple hypotheses but then filtering results to identify only the best matching hypothesis based on signal metrics. This approach achieves high detection accuracy through multiple comparisons while reducing processing complexity by not exhaustively processing all hypotheses equally,而是 selecting the most promising candidates.
Solution Approach 2:
The hypothesis testing process is segmented into distinct stages: initial correlation with multiple hypotheses, metric evaluation, subset identification, and final selection. This segmentation allows the system to maintain high detection accuracy through comprehensive hypothesis testing while managing processing complexity through structured, phased evaluation.
Data Source
AI summary
An illustrated embodiment disclosed herein is a method including correlating, by an endpoint, a first frame and a second frame with a plurality of hypotheses, detecting, by the endpoint, for each correlation of the first frame, a first metric and, for each correlation of the second frame, a second metric, identifying, by the endpoint, a first subset of hypotheses based on the first metric and a second subset of hypotheses based on the second metric, identifying, by the endpoint, pairs of hypotheses, each pair including a first hypothesis from the first subset and a second hypothesis from the second subset. The first hypothesis is same or within a predetermined distance of the second hypothesis. The method includes selecting, by the endpoint and from the pairs of hypotheses, a hypothesis based on the second metric and selecting, by the endpoint, a channel for transmission at which the hypothesis is selected.