User Equipment Receive Beam Information for Machine Learning Channel Prediction
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Solution Overview
Problem
Existing wireless communication systems face limitations in accurately predicting channel characteristics due to the lack of receive beam information from user equipment (UE) being available at network entities, leading to inefficient beam selection and resource utilization.
Innovation Solution
User equipment provides receive beam information to network entities, enabling the training of a machine learning model that predicts channel characteristics, improving beam management and resource allocation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If machine learning models are used for channel prediction without receive beam information, then model training can proceed with available data, but prediction accuracy is insufficient
Solution Approach 1:
The patent introduces receive beam information as an intermediary element that bridges the gap between available channel measurements and accurate channel predictions. The UE determines receive beam information based on channel measurement resources and provides this information to the network entity, which then uses it as additional input for training and applying the machine learning model, thereby improving prediction accuracy without requiring direct access to the UE's internal beamforming state
Solution Approach 2:
The patent applies preliminary action by having the UE determine and provide receive beam information before the channel prediction process occurs. The UE performs channel measurements on reference signals, determines the receive beam information based on these measurements and configured channel measurement resources, and provides this information to the network entity in advance, enabling the ML model to make more accurate predictions
2Productivity
If traditional beam selection methods are used, then system complexity remains low, but resource utilization is inefficient
Solution Approach 1:
The patent implements self-service by enabling the UE to autonomously determine its receive beam information based on channel measurements and configured resources, without requiring complex network-side beam management. The UE independently performs measurements on reference signals, determines the appropriate receive beam information, and provides this information to the network, thereby improving resource utilization while keeping the overall system complexity manageable
Solution Approach 2:
The patent applies parameter changes by introducing receive beam information as a new parameter in the channel prediction process. This additional parameter, derived from channel measurements and channel measurement resource configurations, enhances the ML model's ability to predict channel characteristics accurately, leading to improved resource allocation and beam selection efficiency
Data Source
AI summary
Methods, systems, and devices for wireless communication at a user equipment (UE) are described. A UE may enhance channel state information (CSI)-reference signal (RS) reports to allow receive beam information and associated transmit beam channel characteristics to be transmitted back to a network entity for training a machine learning model. In some examples, the UE may perform implicit reporting of a receive beam by using additional channel measurement resources or sounding reference signal (SRS) resources to associate with different receive beam options such that the UE may avoid disclosing antenna or beaming implementations or causing the network entity to train the machine learning model too diversely. Additionally, or alternatively, the UE may explicitly report the receive beam quantities. In some examples, the network entity may transmit the machine learning model to the UE so that the UE may also perform receive beam prediction.