Data-Driven Beam Pair Prediction for Higher-Frequency Mobility
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Solution Overview
Problem
The selection of uplink and downlink beams in mobile telephony at high frequencies is challenging due to the mobility of units and frequency variations, affecting connectivity and signal strength.
Innovation Solution
A method involving a base station that receives channel state, location, and mobility information to predict beam pairs, transmits configuration information, and adjusts beam pairs based on feedback for improved communication in higher frequency bands.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If beamforming is implemented at high frequencies to enhance connectivity and signal strength, then signal quality and directivity are improved, but beam selection becomes more challenging due to mobility and frequency variations
Solution Approach 1:
The base station performs beam pair prediction in advance using machine learning models, determining candidate beam pairs before actual communication occurs. This preliminary action uses channel state information, location information, and mobility information from the first frequency band to predict suitable beam pairs for the second frequency band, reducing the complexity of real-time beam selection while maintaining reliable connectivity
Solution Approach 2:
The patent introduces an intermediate frequency band (first frequency band) as a mediator to assist beam establishment in the target high frequency band (second frequency band). By using CSI, location, and mobility information from the intermediate band, the system can predict beam pairs for the target band, simplifying the complex beam selection process at high frequencies while ensuring reliable connectivity
2Reliability
If traditional beam selection methods are used at high frequencies, then the system is simpler to implement, but connectivity and signal strength are insufficient
Solution Approach 1:
The base station receives feedback from the WTRU regarding beam pair performance and uses this feedback to update the machine learning model and refine beam pair predictions. This feedback mechanism enables the system to learn from actual communication outcomes and improve beam selection accuracy over time, achieving strong signal strength while managing complexity through adaptive learning rather than exhaustive search
Solution Approach 2:
The system changes the operating parameters by using data from the first frequency band (CSI, location, mobility information) to predict and determine beam pairs for the second frequency band. This parameter transformation approach allows the system to achieve high signal strength at high frequencies by leveraging measurements from lower frequencies, avoiding the need for complex direct high-frequency beam scanning
3Measurement precision
If beam pairs are established using real-time measurements only, then accuracy is high, but the process is time-consuming and inefficient
Solution Approach 1:
The base station performs beam pair prediction in advance using machine learning models trained on historical data from the first frequency band. By determining candidate beam pairs before actual communication in the second frequency band, the system reduces beam establishment time while maintaining accuracy through the predictive power of the ML model that incorporates channel state, location, and mobility information
Solution Approach 2:
The system dynamically adapts by combining predictive beam pair information from machine learning with real-time feedback from the WTRU. The base station can update the beam pair predictions based on actual measurement results, creating a dynamic system that balances pre-computed accuracy with real-time adaptation, thereby reducing overall beam establishment time while maintaining high precision
Data Source
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AI summary
A method performed by a BS includes receiving, from a WTRU in a first frequency band, CSI, location, and mobility information, determining beam prediction information for communication in a second frequency band with the WTRU based on the received information, determining beam pair prediction information to establish a communication in a second frequency band, wherein the second frequency band is a higher frequency than the first, transmitting in the first frequency band configuration information relating to the beam pair prediction information for communication in the second frequency band, wherein the configuration information comprises a codeword index and time slot for each beam pair, transmitting, in the second frequency band, at least one SSB, according to the beam pair prediction information, receiving feedback from the WTRU, and performing either transmitting an acknowledge to the WTRU or updating the beam pair prediction.