Electromagnetic Environment Awareness for Network Resource Optimization
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Solution Overview
Problem
Existing spectrum management systems face challenges in efficiently utilizing the finite wireless communications spectrum due to diverse devices operating at different frequencies and technological standards, leading to difficulties in effective regulation and optimization across global regulations.
Innovation Solution
A system utilizing a Multi-Access Edge Computing (MEC) layer with a wireless network resource optimization application, including a programmable rules and policy editor, a detection engine, and a learning engine, to analyze electromagnetic environments and create actionable data for optimizing network resources by detecting signals of interest and learning the electromagnetic environment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If spectrum management systems regulate diverse devices operating at different frequencies and technological standards, then spectrum utilization efficiency improves, but system complexity increases
Solution Approach 1:
The spectrum management system is designed to handle multiple device types, frequency ranges, and technological standards through a unified platform. The system can simultaneously manage LTE, 5G, and other wireless technologies across different frequency bands, eliminating the need for separate management systems for each technology standard.
Solution Approach 2:
The patent implements a hierarchical spectrum management architecture where higher-level policies and regulations are nested within the system framework, and specific device-level spectrum allocations are nested within those policies. This multi-layered structure allows complex spectrum management requirements to be organized in manageable tiers, reducing operational complexity while maintaining comprehensive control.
2Measurement precision
If spectrum management systems implement comprehensive regulation across global standards, then spectrum allocation accuracy improves, but difficulty of detecting and measuring increases
Solution Approach 1:
The system employs intermediary components including spectrum sensors that detect electromagnetic signals and convert them into measurable data, and data analysis engines that process this information. These intermediaries bridge the gap between raw spectrum signals and actionable management decisions, making the detection and measurement processes more manageable while maintaining high accuracy.
Solution Approach 2:
The spectrum detection and measurement functions are divided into separate modular components: spectrum sensing modules for signal detection, FFT engines for frequency domain analysis, and data analysis engines for processing results. This segmentation allows each component to specialize in specific tasks, improving overall measurement precision while reducing the complexity any single component must handle.
3Productivity
If real-time spectrum analysis is performed to optimize network resources, then resource allocation efficiency improves, but energy consumption increases
Solution Approach 1:
The spectrum management system performs real-time analysis at strategically determined intervals rather than continuously. The system monitors spectrum conditions and triggers analysis when changes are detected or at scheduled intervals, reducing unnecessary energy consumption while maintaining effective resource allocation. This periodic operation allows the system to balance responsiveness with energy efficiency.
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.