Wireless Network Interference Prediction via Device Signal Measurements
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Solution Overview
Problem
Current wireless network interference determination mechanisms are ineffective in predicting potential interference at specific locations, relying on post-facto signal losses or radio link failures and lacking proactive methods to mitigate interference between adjacent access nodes.
Innovation Solution
A method and system that retrieve signal measurements from wireless devices at specific locations to determine potential interference caused by neighboring access nodes, allowing for adjustments such as antenna configuration, operating mode, or scheduling schemes to minimize interference.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If current interference determination mechanisms are used, then interference can be detected after signal losses or radio link failures occur, but proactive interference prediction at specific locations cannot be achieved
Solution Approach 1:
The system performs preliminary actions by collecting signal measurements from wireless devices at specific locations and calculating potential interference values before actual interference occurs. The network node stores these potential interference values in a database, enabling proactive identification of interference-prone locations before signal losses or radio link failures happen, thus resolving the contradiction between detection accuracy and response time.
2Reliability
If signal measurements are collected from wireless devices at specific locations, then potential interference can be predicted proactively, but system complexity increases
Solution Approach 1:
Wireless devices perform self-service by autonomously measuring signal parameters (such as reference signal receive power) from serving and neighboring access nodes at their current locations. The devices then transmit these measurements to the network node, which automatically calculates potential interference values and stores them. This self-service approach enables proactive interference prediction without requiring complex centralized measurement infrastructure, thus resolving the contradiction between prediction capability and system complexity.
3Reliability
If potential interference values are calculated and stored for multiple locations, then interference mitigation can be performed proactively, but information processing and storage requirements increase
Solution Approach 1:
The system applies local quality by calculating and storing potential interference values specifically at discrete geographic locations where wireless devices are measured, rather than attempting to model interference continuously across the entire network coverage area. The network node maintains a database of potential interference values indexed by location, enabling targeted interference mitigation only where needed based on actual measurement data, thus resolving the contradiction between mitigation effectiveness and data processing requirements.
Data Source
AI summary
A potential interference is determined for specific geographic locations of a wireless network based on signal measurements performed by wireless devices at said specific geographic locations. Obtaining power measurements of reference signals sensed at a wireless device at a specific location, and determining a potential interference caused at the specific location based on the power measurements. The power measurements comprise measurements of a reference signal power (RSRP) performed by a wireless device at the specific location. The wireless device may perform multiple measurements of signal power at various locations, and submit to the network measurements recorded at each location. The measurements may be performed periodically or triggered by the network.