Radio Beam Determination Using Probabilistic Historical Data
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Solution Overview
Problem
Multi-antenna systems face challenges in obtaining accurate Channel State Information (CSI) efficiently, particularly in massive MIMO systems, due to high resource requirements and increased overheads in reporting and beam management, especially in scenarios with limited uplink coverage and high-frequency bands like mmWave.
Innovation Solution
A method for determining radio beam configurations using a probabilistic mechanism or algorithm that analyzes historical radio beam configurations and data to estimate candidate configurations for communication with terminal devices, reducing the need for frequent and resource-intensive CSI reporting.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If frequent periodic or aperiodic beam-sweeping operations are performed to obtain accurate CSI, then measurement precision is improved, but device complexity and resource overhead increase significantly
Solution Approach 1:
The network device pre-determines a set of candidate beams and their corresponding downlink reference signal configurations before actual communication. This preliminary preparation allows the terminal to perform measurements more efficiently without requiring frequent exhaustive beam-sweeping operations, thereby reducing beam management complexity while maintaining measurement accuracy.
Solution Approach 2:
The patent uses uplink channel state information as a copy or proxy to infer downlink beam configurations. By leveraging channel reciprocity, the system determines downlink reference signal configurations based on uplink measurements, avoiding the need for extensive downlink beam-sweeping and reducing overall beam management overhead.
2Measurement precision
If terminal devices report detailed measurement reports for beam selection, then measurement precision is improved, but loss of time and uplink resources increase
Solution Approach 1:
The patent extracts only the essential information needed for beam determination from the terminal's measurements. Instead of requiring comprehensive measurement reports, the system uses selective information extraction (such as uplink channel state information) to infer downlink beam configurations, significantly reducing reporting overhead and delay while maintaining beam selection accuracy.
Solution Approach 2:
The network device acts as an intermediary that processes and interprets minimal terminal feedback to determine optimal beam configurations. Rather than relying on detailed terminal reports, the network device uses its own pre-determined candidate beam information combined with simplified terminal feedback to make beam selection decisions, reducing the information exchange burden.
3Productivity
If massive antenna arrays are deployed to improve spectrum efficiency, then productivity is improved, but loss of substance and resource requirements increase
Solution Approach 1:
The patent changes the parameter of beam configuration determination from exhaustive measurement-based approaches to probabilistic prediction-based approaches. By using machine learning models that predict optimal beams based on historical data and current channel conditions, the system achieves high spectrum efficiency with massive MIMO while significantly reducing uplink resource consumption for feedback and reporting.
Solution Approach 2:
Instead of requiring complete and frequent CSI feedback for all antenna elements, the patent uses partial information (such as limited uplink measurements) combined with predictive algorithms to determine beam configurations. This partial action approach maintains high spectrum efficiency for massive MIMO systems while reducing the excessive resource requirements for full CSI reporting.
Data Source
AI summary
Provided is a method in a network device for radio beam determination. The method includes: obtaining current information data related to a terminal device; and estimating a candidate radio beam configuration for communication with the terminal device based on the current information data by using a probabilistic mechanism, algorithm or policy that is obtained by analyzing historical radio beam configurations for communication with the terminal device and history information data related to the terminal.