Inter-Band Reference Signal Estimation for Low-Overhead RF Bands
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing wireless communication systems face challenges in efficiently estimating features of one radio frequency band based on measurements from another band, leading to increased network overhead and power consumption.
Innovation Solution
A method and apparatus for wireless communication that involves receiving assistance information and configuration information for a second band from a first TRP, allowing a UE to estimate features of the second band based on reference signals received in the first band, thereby reducing the need for direct measurements and transmissions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If direct measurements are performed in the second band, then measurement precision is improved, but network overhead and power consumption increase
Solution Approach 1:
The patent uses reference signals transmitted in the first band as an intermediary to estimate channel characteristics in the second band. Instead of directly measuring the second band, the system measures reference signals in the first band and uses machine learning models to infer the second band channel state, thereby reducing power consumption while maintaining acceptable estimation accuracy.
Solution Approach 2:
The system creates a virtual copy of the channel characteristics by training machine learning models using reference signal measurements from the first band. These trained models then generate estimated channel states for the second band, effectively copying the essential channel information without requiring direct physical measurements in the second band.
2Measurement precision
If direct measurements are performed in the second band, then measurement precision is improved, but network overhead increases
Solution Approach 1:
Reference signals in the first band serve as intermediary measurements that provide sufficient information for estimating second band channel characteristics. By using these intermediary signals and machine learning models, the system avoids the need for extensive direct measurements in the second band, thereby reducing network overhead while maintaining estimation precision.
Solution Approach 2:
The system performs preliminary action by training machine learning models in advance using reference signal data from the first band. Once trained, these models can rapidly generate channel estimates for the second band without requiring extensive real-time measurements, thus reducing network overhead during actual operation.
3Loss of information
If reference signals are transmitted for channel estimation, then channel characteristics can be determined, but power consumption increases
Solution Approach 1:
The reference signals transmitted in the first band serve multiple functions: they are used for both first band channel estimation and as training data for machine learning models that estimate second band channel characteristics. This multi-functionality allows the system to acquire necessary channel information while minimizing the number of dedicated reference signal transmissions, thereby reducing power consumption.
Solution Approach 2:
The machine learning models enable the system to self-service by generating channel estimates for the second band based on existing first band reference signal measurements. This self-service capability eliminates the need for additional power-consuming reference signal transmissions specifically for second band estimation.
4Productivity
If collocation information is provided for multiple TRPs, then communication efficiency is improved, but device complexity increases
Solution Approach 1:
The patent uses machine learning models as intermediaries to process collocation information from multiple TRPs. Instead of requiring the UE to directly and complexly process information from multiple TRPs, the machine learning models automatically process this information and generate channel estimates, thereby improving communication efficiency while managing device complexity through intelligent automation.
Data Source
Figure 1
Figure 2
Figure 3
AI summary
A method of wireless communication, by a user equipment (UE), includes receiving, from a first transmission and reception point (TRP) operating in a first band, assistance information comprising collocation information for both a second TRP operating in a second band and a communication node operating in the first band. The method also includes receiving, from the first TRP, configuration information for one or more reference signals (RSs) associated with the communication node. The method further includes communicating with the second TRP based on one or more features of the second band estimated from the one or more RSs.