Real-Time Frequency Map for Dynamic Spectrum Sharing
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The increasing demand for frequency spectrum due to connected devices poses challenges in frequency sharing, particularly in identifying available and optimal frequency bands, especially for remote communication devices, where real-time detection and switching are inefficient and may lead to unreliable communication due to factors like distance, environment, and ionospheric conditions.
Innovation Solution
A system and method for generating a detailed real-time frequency map that collects and analyzes data on unused and optimal frequency bands, including geographical and temporal variations, to provide a list of optimal frequencies for communication, while automatically detecting primary transmitters and updating the frequency map continuously with historical, current, and predicted conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If real-time detection and switching between frequency bands is implemented, then communication reliability is improved, but system complexity and latency increase
Solution Approach 1:
The system pre-generates a list of optimal frequency bands based on historical data, environmental conditions, and predicted trends before actual communication needs arise. This preliminary preparation allows the system to quickly switch to pre-validated frequency bands without performing complex real-time analysis, thereby improving communication reliability while reducing system complexity and latency
Solution Approach 2:
The frequency map is dynamically updated and regenerated based on changing environmental conditions, historical performance data, and predicted future states. The system adapts the frequency band recommendations in real-time without requiring complex switching logic, maintaining reliability while managing system complexity through adaptive rather than reactive changes
2Measurement precision
If detailed frequency map with historical and predicted data is generated, then frequency selection accuracy is improved, but data processing time and computational resources increase
Solution Approach 1:
The system performs comprehensive data collection, historical analysis, and predictive modeling in advance to generate the frequency map before it is needed for actual communication. By pre-processing all relevant data including environmental factors, historical performance, and predictions, the system achieves high frequency selection accuracy without incurring processing delays during critical communication moments
Solution Approach 2:
The frequency map is regenerated periodically or based on triggering events rather than continuously. This periodic update approach maintains frequency selection accuracy by incorporating fresh data while avoiding unnecessary computational overhead and data processing time between updates, as the system only reprocesses data when conditions warrant changes
Data Source
AI summary
System and methods are disclosed for collecting detailed list of frequencies along with any relevant information such as users, time of day, weather, ionospheric conditions, quality of the transmission. This information is used to create a detailed frequency map. The frequency map is continuously updated. The frequency map is used to generate an optimum list of frequency bands that can be used for frequency sharing. Having a real-time frequency map allows for fast and reliable switching between optimum frequencies if a primary user is detected during transmission.