UE LOS/NLOS Transition Prediction for NTN Mobility Handling
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Solution Overview
Problem
Existing mobile communication systems, particularly in non-terrestrial networks (NTN), face challenges with frequent mobility events and varying radio conditions due to satellite movements, leading to unpredictable line-of-sight (LOS) and non-line-of-sight (NLOS) transitions that impact communication performance.
Innovation Solution
User Equipment (UE) is configured to detect and predict radio state transitions by measuring channel conditions, estimating past transitions, and reporting predictions to the network, allowing the network to adjust operations such as handovers and scheduling to optimize communication during LOS/NLOS changes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the network uses traditional reactive approaches to handle radio state transitions, then the system complexity remains low, but the communication reliability deteriorates due to unpredictable LOS/NLOS transitions
Solution Approach 1:
The UE performs preliminary actions by detecting and estimating radio state transitions before they actually occur. The UE measures channel conditions, identifies transition patterns, and sends advance notifications to the network, enabling the network to proactively adjust communication parameters before signal degradation happens, thus improving reliability without requiring complex real-time processing
Solution Approach 2:
The system implements feedback mechanisms where the UE continuously monitors radio conditions, detects LOS/NLOS transitions, and reports these states back to the network. This feedback loop enables the network to adapt communication parameters dynamically based on actual radio state changes, improving communication reliability through informed decision-making
2Productivity
If the UE continuously monitors and reports radio state transitions, then the communication efficiency improves, but the energy consumption increases
Solution Approach 1:
Instead of continuous monitoring, the UE performs radio state detection periodically at configured intervals. The UE measures channel conditions at specific time points, estimates transitions based on these periodic samples, and reports only when transitions are detected. This periodic approach maintains communication efficiency by catching actual transitions while significantly reducing energy consumption compared to continuous monitoring
Solution Approach 2:
The UE performs partial monitoring by focusing only on detecting radio state transitions rather than continuously analyzing all channel parameters. The system configures the UE to monitor specific channel quality indicators relevant to LOS/NLOS transitions, performing sufficient (but not excessive) measurements to detect transitions while minimizing unnecessary energy expenditure on redundant monitoring
3Adaptability or versatility
If the network adjusts communication parameters proactively based on predictions, then the adaptability improves, but the measurement precision requirements increase
Solution Approach 1:
The network performs preliminary adjustments to communication parameters based on advance notifications from the UE about upcoming radio state transitions. By receiving early warnings of LOS/NLOS changes, the network has time to proactively adapt parameters such as modulation schemes, coding rates, and resource allocation before the actual transition occurs, improving network adaptability without requiring ultra-precise real-time measurements
Solution Approach 2:
The system implements beforehand cushioning by maintaining buffer margins and reserve resources based on predicted radio state transitions. The network prepares alternative communication configurations in advance when transition predictions are received, creating a cushion that allows smooth adaptation when transitions actually occur, reducing the need for highly precise real-time measurement and rapid parameter changes
Data Source
AI summary
Systems, methods, apparatuses, and computer program products for utilizing user equipment (UE) detection of radio state conditions. For example, certain embodiments may detect and utilize knowledge of periodic line-of-sight (LOS)/non-LOS (NLOS) radio state changes to improve a network's handling of such radio states. In particular, a UE may be configured to observe LOS/NLOS radio state transitions over time. The UE may generate an estimate of when periodic radio state changes have occurred. The UE may report a prediction of a future LOS/NLOS radio state change based on the estimates of when the previous radio state changes have occurred. The predictions may be reported to the network as a measurement report.