Beam Prediction Using LOS Probability for Future TCI States
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Solution Overview
Problem
Determining the location of wireless transmit/receive units (WTRUs) in wireless networks is challenging due to their mobility and the dynamic nature of the environment and radio signals, especially in mmW communications systems where signal attenuation is high, affecting the accuracy of traditional location-based services.
Innovation Solution
A WTRU predicts beam information by receiving reference signals, estimating line of sight (LOS) probability, and reporting directional information based on speed and position, using CSI-RS measurements to determine future TCI states and send predictions to the network.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional location determination methods using dedicated signaling are used, then location information can be obtained, but the accuracy deteriorates due to WTRU mobility and dynamic environment
Solution Approach 1:
The patent applies preliminary action by having the WTRU predict future beam information and TCI states in advance based on current position, speed, and LOS probability. This allows the system to proactively determine future beam configurations rather than reacting to location changes after they occur, improving both accuracy and reliability of location-based services in mobile environments
Solution Approach 2:
The patent implements feedback mechanisms where the WTRU reports predicted beam information and TCI states back to the network. This feedback loop allows the network to verify predictions and adjust beam configurations accordingly, enhancing the reliability of location determination while maintaining high accuracy despite WTRU mobility
2Reliability
If beamformed transmissions are used to overcome path loss in mmW communications, then signal quality improves, but the complexity of beam management increases
Solution Approach 1:
The patent reduces beam management complexity by having the WTRU predict future beam information in advance based on its current position, speed, and LOS probability estimates. This allows the network to pre-configure beams before the WTRU actually needs them, reducing real-time computational complexity while maintaining high signal quality through accurate beamforming
Solution Approach 2:
The patent applies dynamics by enabling the beam configuration to adapt dynamically to changing WTRU conditions. The WTRU continuously updates its position, speed, and LOS probability estimates, which then dynamically adjust the predicted beam configurations. This dynamic adaptation maintains optimal signal quality while managing complexity through automated, data-driven adjustments
3Measurement precision
If the WTRU reports detailed beam predictions with multiple parameters, then the accuracy of beam selection improves, but the signaling overhead increases
Solution Approach 1:
The patent applies local quality by selectively reporting only the most critical beam prediction parameters depending on the specific communication conditions. Instead of always reporting all possible parameters, the WTRU adjusts the level of detail based on local conditions such as mobility speed, LOS probability, and current beam configuration, thereby reducing unnecessary signaling overhead while maintaining sufficient accuracy for effective beam selection
Data Source
AI summary
A WTRU may be configured to receive first configuration information associated with a channel state information reference signal (CSI-RS) resource set, a set of transmission configuration index (TCI) states, a set of probability thresholds, and/or a set of time durations. The WTRU may be configured to estimate a line of sight (LOS) probability of the WTRU based on one or more CSI-RS measurements. The WTRU may be configured to determine whether the estimated LOS probability is greater than or equal to a probability threshold from the set of probability thresholds. In response to determining that the estimated LOS probability is greater than or equal to the probability threshold, the WTRU may be configured to determine a time duration from the set of time durations based on the estimated LOS probability. The WTRU may be configured to predict a future TCI state applicable to an associated time instance.