Downlink Interference Detection Using Aggressor Cell Identification
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Downlink interference in wireless telco networks, such as LTE, causes degraded quality of service for users due to overlapping signals from neighboring base stations, making it challenging to detect and address the aggressor cells causing interference.
Innovation Solution
A network analysis platform uses pre-trained performance models based on historical telemetry data to compare actual and expected downlink performance, identifying downlink interference by normalizing interference factors and determining overshooting aggressor cells with excessive overlap, which are then indicated for power and tilt configuration adjustments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If cellular networks continue to densify to extract performance from all allocated bandwidths, then network capacity and coverage are improved, but downlink interference becomes more pervasive and problematic
Solution Approach 1:
The patent segments the network analysis into multiple components: interference detection module, aggressor cell identification module, and configuration adjustment module. This allows the system to handle the complexity of interference management in dense networks by breaking down the problem into manageable parts that can be addressed systematically
Solution Approach 2:
The system changes key parameters such as electronic tilt angles and transmit power levels of aggressor cells to reduce interference. By dynamically adjusting these parameters based on detected interference conditions, the network can maintain high capacity while mitigating the harmful effects of downlink interference in dense deployments
2Area of stationary object
If a neighboring base station transmits at a power level that is too high to expand coverage, then coverage area is improved, but signal overlap with serving base station causes downlink interference
Solution Approach 1:
The patent applies local quality by adjusting the electronic tilt angle of the aggressor cell's antenna array to create a non-uniform radiation pattern. This focuses the signal in specific directions while reducing it in others, allowing coverage expansion in desired areas while minimizing signal overlap and interference in conflicting areas
Solution Approach 2:
The system dynamically adjusts transmit power and tilt configurations based on real-time interference detection. The electronic tilt angle is changed from a static parameter to a dynamic one that can be optimized to balance coverage expansion with interference mitigation, allowing the network to adapt to changing conditions
3Area of stationary object
If electronic tilt angle is configured to expand coverage area, then coverage is improved, but overlap with serving base station signal causes downlink interference
Solution Approach 1:
The patent uses electronic tilt to create localized signal distribution patterns, concentrating coverage in specific geographic areas while reducing signal strength in overlapping regions. This allows the aggressor cell to expand its effective coverage area without causing excessive interference to the serving cell's coverage zone
4Reliability
If downlink interference is detected and aggressor cells are identified, then interference management is improved, but network complexity increases
Solution Approach 1:
The patent implements self-service by enabling the network to automatically detect interference, identify aggressor cells, and adjust configurations without manual intervention. The system uses machine learning models and automated algorithms to manage interference independently, reducing the operational complexity for network operators while improving reliability
Data Source
AI summary
A system can include a network analysis platform that applies models to identify downlink interference at a network cell, such as at a base station. For a session at a cell, an expected performance with normalized downlink interference can be compared to an actual performance to determine whether the session is impacted. This can include normalizing channel quality index (“CQI”) and negative-acknowledgement (“NACK”) rate. Overshooting aggressor cells can be identified as the source of the downlink interference based on a useless overlap fraction exceeding a threshold. The impacted sessions and root causes can be displayed on a graphical user interface (“GUI”).