5G NR Signal Quality Optimization via Image-Based Interference Detection
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Solution Overview
Problem
The management of 5G wireless access networks is complicated by the need for optimal antenna array settings to minimize interference and maximize signal quality, especially in non-line of sight scenarios with mm-wave frequency signals experiencing multipath propagation and fading due to environmental factors.
Innovation Solution
A computer system is configured to obtain and analyze image data to identify sources of interference for 5G NR wireless signals, estimate signal quality, and generate recommendations for Self-Organizing Network (SON) actions, such as adjusting antenna tilt or power distribution parameters, using machine learning models to improve signal quality and coverage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual optimization of antenna array settings is performed, then signal quality can be improved, but network management complexity increases
Solution Approach 1:
The system implements self-service by enabling the network to automatically optimize its own antenna array settings through machine learning models that analyze signal data and generate configuration recommendations without human intervention, thereby improving signal quality while reducing management complexity
Solution Approach 2:
The system employs feedback mechanisms by continuously monitoring signal quality metrics and using this information to dynamically adjust antenna array configurations through automated optimization algorithms, creating a closed-loop system that maintains high signal quality without increasing operational complexity
2Ease of operation
If automated optimization systems are implemented, then network management complexity is reduced, but system complexity increases
Solution Approach 1:
The system replaces manual mechanical configuration processes with automated electronic optimization systems that use machine learning algorithms to analyze signal data and generate antenna array settings, thereby simplifying network management operations while concentrating system complexity in the automated optimization module
Solution Approach 2:
The system introduces an intermediary automated optimization layer between network operators and antenna array configurations, using machine learning models as mediators that translate operational requirements into technical parameters, thereby easing operator burden while managing system complexity through abstraction
3Reliability
If real-time signal optimization is performed, then signal quality improves, but processing time and computational resources increase
Solution Approach 1:
The system performs preliminary actions by pre-processing signal data and pre-computing optimization parameters using machine learning models trained on historical data, enabling faster real-time decision-making while maintaining high signal quality through预先 prepared optimization strategies
Solution Approach 2:
The system applies partial optimization by focusing computational resources on the most critical signal parameters and antenna configurations that have the greatest impact on signal quality, rather than optimizing all parameters equally, thereby reducing processing time while maintaining effective signal optimization
Data Source
AI summary
A computer system may include a memory storing instructions and processor configured to execute the instructions to obtain image data relating to a path of Fifth Generation (5G) New Radio (NR) wireless signals sent or received by a base station; analyze the obtained image data to identify sources of interference for the 5G NR wireless signals; and estimate a quality of the 5G NR wireless signals along the path based on the identified sources of interference. The processor may be further configured to determine that the estimated quality of the 5G NR wireless signals is less than a quality threshold; generate a recommendation for a self-organizing network (SON) action relating to the base station, based on determining that the estimated quality of the 5G NR wireless signals is less than the quality threshold; and perform the SON action relating to the base station based on the generated recommendation.