Spectrum Signal Classification for Real-Time Wireless State Detection
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Solution Overview
Problem
Existing spectrum management devices are limited by their specificity to certain technologies, bulkiness, high cost, difficulty in use, and lack of real-time data analysis, making them inefficient for managing diverse wireless communications spectrum needs.
Innovation Solution
A system that automatically identifies and classifies wireless signals in near real-time using radio frequency measurements, providing real-time analytics and identifying open spaces for communication by analyzing signal characteristics, protocols, and origins, without requiring external connectivity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If narrowly tailored spectral analyzer devices are used for specific communication standards, then measurement precision for that specific standard is improved, but adaptability to other technologies and spectrum uses deteriorates
Solution Approach 1:
The patent applies universality by designing a spectral analyzer that can handle multiple communication standards and spectrum uses through a single device. The system uses a database of signal characteristics and classification algorithms that can identify and analyze various signal types (cellular, Wi-Fi, radar, TV, etc.) without requiring separate specialized devices for each standard, thus achieving both precision and versatility.
Solution Approach 2:
The patent utilizes parameter changes by dynamically adjusting analysis parameters based on the detected signal type. The system modifies its classification criteria, frequency ranges, and measurement parameters according to the identified communication standard or signal characteristics, enabling accurate analysis across diverse technologies through parameter adaptation rather than hardware changes.
2Adaptability or versatility
If comprehensive spectrum management devices are designed to handle all technologies, then adaptability is improved, but device complexity and bulkiness increase
Solution Approach 1:
The patent applies segmentation by dividing the spectrum management function into modular components: a signal detection module, a database of signal characteristics, a classification module, and an analysis module. Each component handles specific aspects of spectrum management independently, allowing the system to process multiple technologies through organized, discrete functional blocks rather than a monolithic complex structure.
Solution Approach 2:
The patent uses an intermediary approach by introducing a database of signal characteristics as a mediator between raw signal detection and classification decisions. This database stores reference information about various communication standards and signal patterns, enabling the system to compare detected signals against stored knowledge without requiring complex real-time analysis algorithms for each standard, thus reducing computational complexity.
3Reliability
If traditional spectrum management systems are used, then reliability is improved, but productivity and real-time analysis capability deteriorate
Solution Approach 1:
The patent applies preliminary action by pre-storing signal characteristics, patterns, and classification criteria in a database before actual spectrum analysis occurs. This pre-prepared reference information enables rapid comparison and identification of signal types during real-time operation, eliminating the need for complex on-the-fly analysis and significantly improving processing speed while maintaining reliability through use of pre-validated classification criteria.
4Measurement precision
If external connectivity to remote databases is required for analysis, then measurement precision is improved, but ease of operation and portability deteriorate
Solution Approach 1:
The patent applies self-service by embedding the complete spectrum analysis capability within the portable device itself. The device includes an onboard database of signal characteristics and all necessary classification algorithms, enabling it to perform comprehensive spectrum analysis independently without requiring external connectivity. This self-contained design maintains measurement precision while dramatically improving portability and ease of operation.
Data Source
AI summary
Systems, methods, and apparatus are provided for automated identification of baseline data and changes in state in a wireless communications spectrum, by identifying sources of signal emission in the spectrum by automatically detecting signals, analyzing signals, comparing signal data to historical and reference data, creating corresponding signal profiles, and determining information about the baseline data and changes in state based upon the measured and analyzed data in near real time, which is stored on each apparatus or device and/or on a remote server computer that aggregates data from each apparatus or device.