RAN Paging Prediction Using UE Velocity Vectors
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Solution Overview
Problem
Current wireless communication networks face challenges in efficiently managing the mobility of user equipment (UE) in RRC_INACTIVE state, particularly when UE is in motion, leading to inefficient UE context transfer and frequent RNA updates, resulting in increased overhead and latency in reestablishing RRC connections across different radio access network (RAN) areas.
Innovation Solution
The system predicts the location and route of a UE based on velocity and time-lapse information, allowing for smart paging by sending paging requests to predicted RNAs along the UE's route, either sequentially or in parallel, using a route and velocity information matrix to improve RNA selection and reduce overhead.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the network sends paging messages to all possible base stations when UE is in RRC_INACTIVE state, then the UE can be reached regardless of location, but the signaling load and network overhead increase significantly
Solution Approach 1:
The base station performs preliminary actions by storing the UE's velocity vector and trajectory information when the UE enters RRC_INACTIVE state. This advance preparation enables the network to predict the UE's future location and send paging messages only to relevant base stations, rather than broadcasting to all possible base stations, thereby reducing signaling load while maintaining reliable UE reachability
Solution Approach 2:
The system utilizes the UE's own movement characteristics (velocity vector) that the UE provides during normal operation to enable the network to independently track and locate the UE without requiring continuous UE-initiated position updates. The UE's motion data serves the dual purpose of both mobility management and location tracking
2Measurement precision
If the network frequently updates RNA information for moving UE, then the UE location accuracy is maintained, but the overhead and latency increase
Solution Approach 1:
The base station performs preliminary location prediction using stored velocity vector information before the UE actually moves to a new location. By calculating the predicted location in advance based on velocity and direction, the network maintains accurate UE location knowledge without requiring frequent real-time updates, thus reducing latency while preserving location accuracy
Solution Approach 2:
The system uses feedback from the UE's provided velocity vector information to continuously refine location predictions. The velocity data serves as feedback that enables the base station to update the UE's predicted location dynamically, maintaining accuracy without frequent explicit location reporting from the UE
3Measurement precision
If the base station stores detailed UE movement information, then the prediction accuracy improves, but the memory requirements and processing complexity increase
Solution Approach 1:
The base station extracts only the essential elements needed for prediction - the velocity vector (magnitude and direction) - from the UE's movement data. By focusing on this key parameter rather than storing complete trajectory histories or detailed position reports, the system achieves sufficient prediction accuracy while minimizing memory requirements and processing complexity
Solution Approach 2:
The system transforms detailed position information into a simplified velocity vector representation. By changing the parameter from absolute position coordinates to relative velocity (speed and direction), the base station reduces data storage requirements while maintaining the ability to predict future locations through simple vector addition calculations
Data Source
AI summary
A system includes a user equipment (UE) traveling at least at a predetermined velocity. The UE is in RRC_INACTIVE state since time T. The system further includes at least a first base station and a second base station. The first base station receives an RRC_INACTIVE state message from the UE. The RRC_INACTIVE state message includes a location and a velocity of the UE, and a time-lapse, which is an elapsed duration since T. In response to a paging message from a core network, the first base station predicts a location of the UE. In response to the UE being within range of the first base station, the first base station sends the paging message to the UE. In response to the UE being within range of the second base station, the first base station sends a request to the second base station to send the paging message to the UE.