Adaptive Cell Measurement Filtering for Fast Fading Channels
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
In wireless communication networks, especially in LTE, the filtered cell measurements can lag behind instantaneous measurements in fast fading channel conditions, leading to delayed event reporting and potential call drops due to the weighting of earlier samples.
Innovation Solution
Adaptive filtering is implemented by modifying the network-configured filter coefficient based on current fading conditions, allowing for more reflective and timely filtered measurements, which can trigger event reporting and handovers more quickly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Stability of the object's composition
If a network configured filter coefficient is used to calculate filtered measurements, then measurement stability is improved, but measurement responsiveness deteriorates in fast fading channel conditions
Solution Approach 1:
The patent implements adaptive filtering that dynamically adjusts the filter coefficient based on detected fading conditions. When fast fading is detected through analysis of instantaneous measurement samples, the system switches to a modified filter coefficient that reduces weighting of historical samples, thereby adapting the measurement filtering behavior to current channel conditions and resolving the contradiction between stability and responsiveness.
Solution Approach 2:
The system changes the filter coefficient parameter based on detected fading conditions. By monitoring the variation in instantaneous measurement samples and comparing against threshold criteria, the system modifies the filter coefficient from a static network-configured value to a dynamic adaptive value, enabling the filtered measurement to respond more quickly to fast fading while maintaining stability when conditions are favorable.
2Measurement precision
If filtered measurements weight earlier samples heavily, then measurement accuracy is improved, but event reporting delay increases
Solution Approach 1:
The system dynamically adjusts the weighting of historical samples based on detected fading conditions. In fast fading scenarios, the adaptive filter coefficient reduces the weight given to earlier samples, allowing the filtered measurement to track current channel conditions more closely and trigger events timely. In stable conditions, the full weighting is applied to maintain measurement accuracy.
Solution Approach 2:
The system implements a feedback mechanism where instantaneous measurement samples are continuously monitored to detect fading conditions. Based on this feedback, the filter coefficient is adjusted in real-time, creating a closed-loop system that balances measurement accuracy with event reporting timeliness according to actual channel conditions.
3Device complexity
If a standard filter coefficient is used for all conditions, then device complexity is reduced, but adaptability to fading conditions deteriorates
Solution Approach 1:
The system implements self-service adaptive filtering where the wireless communication device autonomously detects fading conditions by analyzing its own instantaneous measurement samples and automatically adjusts the filter coefficient accordingly. This eliminates the need for complex network-side adaptation mechanisms while improving adaptability to varying channel conditions through device-side intelligence.
Solution Approach 2:
The device uses feedback from its own measurement samples to detect fading conditions and trigger adaptive filtering. By monitoring the variation in instantaneous samples and comparing against predefined criteria, the system self-adjusts the filter coefficient without requiring external control, achieving adaptability with minimal added complexity.
Data Source
AI summary
A method for adaptive filtering of cell measurements is provided. The method can include a wireless communication device determining based on instantaneous measurement samples of a cell captured over a measurement period that a fading condition of the cell exceeds a threshold. The method can further include the wireless communication device modifying a network configured filter coefficient to derive a modified filter coefficient in response to the fading condition of the cell exceeding the threshold over the measurement period. The method can additionally include the wireless communication device filtering the instantaneous measurement samples based on the modified filter coefficient to calculate a filtered measurement of the cell. The method can also include the wireless communication device calculating an adjusted measurement value for the cell based on the filtered measurement. The method can further include the wireless communication device using the adjusted measurement value for event evaluation and reporting.