Spectrum Management Device Near Real-Time Analysis
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Solution Overview
Problem
Current spectrum management devices face challenges such as limited capability to handle multiple technological standards, complexity in adapting to changes, high costs, bulkiness, and the inability to provide real-time or near real-time data analysis, leading to inefficient spectrum utilization and management.
Innovation Solution
A system and method for identifying, classifying, and cataloging radio frequency signals in a wireless communications spectrum, using a device with processors, sensors, and receivers to analyze signals in near real-time, providing remote access to data through a virtualized computing network, and identifying available frequencies and signal characteristics.
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 standards and spectrum changes deteriorates
Solution Approach 1:
The patent implements a universal spectral analyzer that can measure multiple communication standards (cellular, Wi-Fi, radar, TV, etc.) within a single device. The system uses a wideband receiver capable of tuning across multiple frequency bands and communication protocols, eliminating the need for separate specialized devices for each standard while maintaining measurement precision through software-defined signal processing.
Solution Approach 2:
The system dynamically changes operating parameters including frequency tuning range, bandwidth, and signal processing algorithms based on the detected communication standard. The receiver can switch between different frequency bands and modulation types, and the processor adapts its analysis methods to match the specific standard being measured, thereby maintaining precision across diverse applications.
2Adaptability or versatility
If conventional spectral management devices are used, then comprehensive spectrum analysis capability is improved, but device complexity and bulkiness increase
Solution Approach 1:
The patent extracts the core spectral analysis functionality from complex conventional devices and implements it in a simplified platform. By using a modular architecture with a generic receiver, programmable processor, and standardized interface, the system removes unnecessary hardware components while retaining comprehensive spectrum analysis capabilities across multiple standards and applications.
Solution Approach 2:
Instead of using multiple specialized hardware devices, the system creates virtual copies of analysis functions through software. The processor executes different analysis algorithms and protocols as software modules, allowing comprehensive spectrum management through virtualization rather than physical complexity.
3Productivity
If real-time spectrum analysis is performed locally, then productivity and response time are improved, but loss of information through data storage requirements increases
Solution Approach 1:
The system extracts only the essential spectral information and key events from the continuous stream of RF data. Instead of storing all raw data, the processor identifies and stores only significant findings such as detected signals, interference events, and spectrum usage patterns, dramatically reducing storage requirements while maintaining real-time analysis productivity.
Solution Approach 2:
The system applies different processing quality levels to different data segments. High-resolution analysis is applied only to periods when significant activity is detected, while lower-resolution or summarized processing is applied to quiet periods, optimizing the balance between real-time response and data storage efficiency.
4Adaptability or versatility
If connectivity to remote servers is required for analysis, then adaptability to cloud processing is improved, but loss of time for data transmission and processing increases
Solution Approach 1:
The system performs preliminary spectral analysis and data processing locally at the point of measurement before any remote transmission occurs. The onboard processor completes the primary detection, classification, and initial analysis functions locally, so that when data is transmitted to remote servers, only summarized results or critical raw data need to be sent, minimizing transmission time and maintaining cloud adaptability.
Data Source
AI summary
Systems, methods, and apparatus are provided for automated geolocation of a signal using 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.