Predictive UE Mobility Pre-Preparation for Low-Latency Handover
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Solution Overview
Problem
Conventional wireless systems have limited UE mobility information, leading to significant signaling overhead and delay due to the need for post-measurement handovers and lack of predictive mobility management.
Innovation Solution
A network entity predicts the UE's mobility by determining the time of entering and duration of stay in each cell along a predicted route, transmitting mobility prediction information to the UE, which includes scheduled actions and parameters for seamless communication.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If conventional post-measurement handover methods are used, then the system maintains simplicity in mobility management, but signaling overhead and delay increase significantly
Solution Approach 1:
The network entity performs preliminary actions by predicting the UE's future location and pre-configuring target cells before the UE actually needs to handover. This includes determining predicted route, calculating predicted time of entering and duration of stay in each cell, and transmitting mobility prediction information in advance, thereby reducing handover delay while maintaining manageable complexity through automated prediction algorithms
2Productivity
If predictive mobility management is implemented, then handover delay is reduced, but signaling overhead increases due to additional prediction information exchange
Solution Approach 1:
The system transmits mobility prediction information containing scheduled actions and parameters in advance, enabling the UE to perform RACH-less access and direct data transmission without repeated signaling exchanges during actual handover, thereby improving mobility management efficiency while the pre-transmitted information reduces subsequent signaling overhead
Solution Approach 2:
The UE uses the received mobility prediction information to autonomously configure itself and perform handover actions without extensive network signaling, reducing signaling overhead while maintaining high mobility management efficiency through self-service mechanisms
3Loss of time
If RACH-less access is enabled through prediction, then latency is reduced for URLLC, but the system requires more precise prediction accuracy
Solution Approach 1:
The network entity performs preliminary prediction of UE mobility parameters including predicted route, predicted time of entering, and predicted duration of stay in each cell before URLLC transmission, enabling RACH-less access that reduces latency while the comprehensive prediction parameters ensure sufficient accuracy for precise resource allocation
Solution Approach 2:
The system changes and optimizes multiple prediction parameters simultaneously (route, time of entering, duration of stay) to achieve the required precision for RACH-less access, thereby reducing URLLC latency while maintaining accurate prediction through multi-parameter optimization
Data Source
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AI summary
A method for UE mobility based on route prediction and pre-preparation. A method for resource allocation in a wireless network includes obtaining, at a network entity, a predicted route for a user equipment (UE). The method also includes determining, by the network entity, a predicted time of entering and a predicted duration of stay of the UE in each of a plurality of cells. Each of the plurality of cells includes a gNB. The method also includes determining, by the network entity, mobility prediction information according to the predicted time of entering and the duration of stay of the UE in each of the plurality of cells. The method also includes transmitting, by the network entity, the mobility prediction information to the UE.