Electromagnetic Environment Analysis for Real-Time Spectrum Allocation
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Solution Overview
Problem
Effective spectrum management is hindered by the diverse nature of wireless signal propagations across different frequencies and technological standards, and the growing demand for spectrum exceeds the finite available resources, necessitating efficient utilization.
Innovation Solution
A system utilizing monitoring sensors, FFT engines, data analysis engines, and Multi-Access Edge Computing (MEC) layers to analyze electromagnetic environments, detect signals of interest, and optimize network resources through programmable rules and policy editors, enabling real-time adjustments to enhance spectrum utilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If spectrum management systems attempt to manage all wireless signals across different frequencies and standards, then spectrum utilization improves, but system complexity increases significantly
Solution Approach 1:
The system segments the complex spectrum management task by separating signal monitoring, analysis, and optimization functions into distinct modules. Monitoring sensors capture raw signals, FFT engines perform frequency domain transformation, data analysis engines process the transformed data, and MEC layers execute optimization actions. This segmentation allows each component to specialize in specific frequency ranges or signal types, improving overall spectrum utilization while keeping individual component complexity manageable.
Solution Approach 2:
The patent introduces intermediate processing layers (FFT engines and data analysis engines) that mediate between raw signal monitoring and final optimization decisions. These intermediaries transform complex multi-standard signals into standardized frequency domain representations, enabling the MEC layer to make informed decisions without directly handling the complexity of diverse wireless standards and frequencies.
2Productivity
If real-time spectrum analysis is performed on all signals, then network resource optimization improves, but processing time and computational load increase
Solution Approach 1:
The system performs preliminary signal transformation using FFT engines to convert time-domain signals into frequency-domain representations before detailed analysis. This preliminary action organizes the signal data in a more analyzable format, enabling the data analysis engines to quickly identify spectrum opportunities and the MEC layer to make rapid optimization decisions, thereby reducing overall processing time while maintaining real-time capability.
3Measurement precision
If the system monitors and analyzes all electromagnetic signals, then spectrum management accuracy improves, but measurement and detection difficulty increases
Solution Approach 1:
The patent replaces direct time-domain signal analysis with frequency-domain analysis using FFT transformation. This substitution converts the difficult task of detecting and measuring complex multi-standard signals in the time domain into a more manageable frequency domain representation, where spectrum occupancy, signal frequencies, and bandwidths are more easily identified and measured with higher precision.
Data Source
AI summary
Systems, methods, and apparatuses for providing optimization of network resources. The system is operable to monitor the electromagnetic environment, analyze the electromagnetic environment, and extract environmental awareness of the electromagnetic environment. The system extracts the environmental awareness of the electromagnetic environment by including customer goals. The system is operable to use the environmental awareness with the customer goals and/or user defined policies and rules to extract actionable information to help the customer optimize the network resources.