Adaptive Reference Signal Prediction for Wireless Beam Management
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Solution Overview
Problem
Existing solutions for beam management in wireless communication networks are inefficient due to high overhead, which affects the performance of reference signal prediction.
Innovation Solution
A user device and network device configuration that enables reference signal measurement and prediction adaptation in time, allowing for implicit determination of time instances and dynamic adjustment of measurement and prediction tasks based on success or failure indications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If beam prediction using neural network is applied, then beam management performance is improved, but overhead is increased
Solution Approach 1:
The patent applies dynamics by making the reference signal transmission pattern adaptive and time-varying. The network dynamically adjusts between full measurement time instances and prediction-only time instances based on prediction accuracy and overhead reduction goals, transforming a static signaling system into a dynamic one that optimizes performance over time.
Solution Approach 2:
The patent implements periodic action through the alternating transmission of reference signals at different time instances. Full reference signals are transmitted at some time instances for accurate measurement, while prediction-only transmission occurs at other time instances, creating a periodic pattern that balances accuracy and overhead reduction.
2Measurement precision
If reference signal measurement is performed at all time instances, then measurement accuracy is improved, but overhead is increased
Solution Approach 1:
The patent applies partial action by performing full reference signal measurements only at selected time instances rather than all time instances. At prediction-only time instances, the system uses predicted values instead of actual measurements, reducing the total measurement overhead while maintaining sufficient accuracy through strategic measurement sampling.
Solution Approach 2:
The patent implements feedback mechanisms where the network evaluates prediction accuracy and uses this information to adjust future transmission patterns. The feedback loop allows the system to learn from previous predictions and measurements, optimizing the balance between measurement frequency and overhead reduction over time.
Data Source
AI summary
Various example embodiments relate to a solution for enhanced reference signal prediction. A user device may be configured to perform both a reference signal measurement and reference signal prediction for at least one time instance for validating the reference signal prediction.