Priority-Based Spectrum Management Using Semantic Rules and Sensing
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Solution Overview
Problem
Existing spectrum management systems face challenges in efficiently managing the finite wireless communications spectrum due to diverse devices operating at different frequencies and technological standards, leading to difficulties in optimizing spectrum usage and accommodating growing demand.
Innovation Solution
A system for dynamic, prioritized spectrum utilization management that includes monitoring sensors, data analysis engines, and a semantic engine to detect, learn, and allocate electromagnetic spectrum based on customer-defined rules and policies, optimizing resource allocation for customer applications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional static spectrum allocation methods are used, then regulatory compliance is maintained, but spectrum utilization efficiency deteriorates due to inability to adapt to dynamic demand
Solution Approach 1:
The patent implements dynamic spectrum allocation by continuously monitoring spectrum usage and automatically adjusting frequency band assignments in real-time based on detected demand, transitioning from static regulatory allocation to adaptive dynamic management that optimizes utilization while maintaining compliance
Solution Approach 2:
The patent introduces an intermediary spectrum management system that acts as a mediator between regulatory requirements and actual spectrum usage, using AI/ML algorithms to interpret both regulatory constraints and real-time spectrum conditions, then making intelligent allocation decisions that satisfy both sides
2Quantity of substance
If more frequency bands are allocated to accommodate growing wireless demand, then service capacity increases, but spectrum scarcity and interference problems worsen
Solution Approach 1:
The patent changes the allocation parameters dynamically by adjusting which frequency bands are assigned to which services based on real-time conditions, using AI/ML to optimize parameter sets that maximize capacity while minimizing interference between different wireless systems
Solution Approach 2:
The patent applies local quality optimization by allowing different frequency bands to be allocated to different geographic locations and service types based on local spectrum conditions and demand, rather than applying uniform allocation rules everywhere, thereby increasing overall capacity while managing interference locally
3Productivity
If real-time spectrum monitoring is implemented across all frequency bands, then spectrum utilization optimization improves, but system complexity and processing requirements increase
Solution Approach 1:
The patent segments the spectrum monitoring task by dividing the electromagnetic spectrum into different frequency bands and assigning specialized monitoring functions to each segment, using AI/ML models optimized for specific band characteristics, thereby reducing overall system complexity while maintaining comprehensive monitoring capability
Solution Approach 2:
The patent implements self-service monitoring where the spectrum management system automatically detects spectrum conditions, identifies optimization opportunities, and executes allocation adjustments without human intervention, using AI/ML algorithms that continuously learn from spectrum data and improve optimization automatically
Data Source
AI summary
Systems, methods, and apparatuses for providing dynamic, prioritized spectrum utilization management. The system includes at least one monitoring sensor, at least one data analysis engine, at least one application, a semantic engine, a programmable rules and policy editor, a tip and cue server, and/or a control panel. The tip and cue server is operable utilize the environmental awareness from the data processed by the at least one data analysis engine in combination with additional information to create actionable data.