Geo-location Database Consistency Checking for Cognitive Radio
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Inconsistent channel availability results between geo-location databases due to differing protection algorithm interpretations, geo-spatial reference points, and update timing issues, leading to potential interference with protected devices in cognitive radio communication systems.
Innovation Solution
An automated consistency checking mechanism that compares and synchronizes results across multiple geo-location databases, allowing for minor spatial and temporal discrepancies while ensuring overall consistency, using a unified or split database architecture to maintain accurate and reliable channel availability information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple geo-location databases are used to determine channel availability, then service coverage and accessibility are improved, but consistency and reliability of results deteriorate due to differing algorithms and update timing
Solution Approach 1:
The system implements automated consistency checking that continuously monitors and compares results from multiple geo-location databases. When inconsistencies are detected, the system generates notifications and enables corrective actions, creating a closed-loop feedback mechanism that maintains reliability while using multiple databases for service coverage
Solution Approach 2:
The patent introduces an intermediary consistency checking mechanism that mediates between multiple geo-location databases. This intermediary layer compares results from different databases, identifies inconsistencies, and provides a unified reliable output, allowing the system to benefit from multiple databases without suffering from their inconsistencies
2Reliability
If automated consistency checking is implemented across multiple databases, then reliability and consistency of channel availability results are improved, but system complexity and computational overhead increase
Solution Approach 1:
The consistency checking system is segmented into modular functional components: database query interfaces, result comparison engines, discrepancy detection modules, and notification systems. This segmentation allows the complex consistency checking function to be implemented as independent, manageable modules that can be selectively activated based on operational needs
Solution Approach 2:
The system implements consistency checking at selective levels rather than exhaustive verification of all parameters. It focuses on checking critical consistency aspects (channel availability determinations) while allowing minor variations in non-critical parameters, reducing computational overhead while maintaining essential reliability
3Measurement precision
If strict consistency verification is applied across all databases, then accuracy of channel availability information is improved, but processing time and operational efficiency decrease
Solution Approach 1:
The system applies different verification strictness levels to different geographic locations and database pairs. High-accuracy verification is applied to critical locations or databases with known issues, while standard verification is applied elsewhere, optimizing the balance between accuracy and processing efficiency through localized quality control
Data Source
AI summary
An apparatus and method of providing accurate and consistent open spectrum results for secondary devices from different geo-location databases is presented. The results, which may be independently derived by each database, are independent of the database queried. The comparison permits some amount of latitude in spatial and temporal consistency between the databases as errors are only indicated if the temporal or spatial discrepancies are pervasive. In addition, large percentages of different locations showing discrepancies when compared also lead to corrective action being taken. Corrective actions that may be taken include forcing problematic databases to update, shunting requests by secondary devices in the problematic locations to acceptable databases or shutting down the problematic databases entirely.