User Equipment-Centric Predictive Mobility for Traffic-Aware Handover
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Solution Overview
Problem
Existing handover procedures in 3GPP networks are inefficient in predicting and ensuring quality of service due to reliance on signal measurements alone, leading to potential service interruptions and suboptimal cell selection based on unknown traffic loads.
Innovation Solution
Implementing user-centric predictive mobility with subnetwork support, where managing UEs share service information within and across subnetworks to assist in handover decisions, reducing reliance on network signaling and improving QoS predictions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If handover decisions are based solely on signal measurements, then the handover procedure is simple to implement, but the quality of service prediction accuracy deteriorates due to unknown traffic loads
Solution Approach 1:
The patent introduces managing UEs as intermediaries between the network and other UEs. These managing UEs collect, aggregate, and share service information (traffic load, QoS metrics) with peer UEs, enabling accurate QoS predictions without requiring complex network signaling for each handover decision. This intermediary layer resolves the contradiction by providing rich information context while keeping individual UE implementations relatively simple.
Solution Approach 2:
The patent implements feedback mechanisms where UEs share their experienced service information (traffic load, QoS measurements) with managing UEs and peer UEs. This feedback loop allows the system to continuously improve QoS prediction accuracy by incorporating real-world performance data from multiple UEs, transforming static signal-based handover decisions into dynamic, experience-driven decisions.
2Reliability
If traditional handover procedures are used without predictive information, then network signaling overhead is reduced, but service interruptions increase due to suboptimal cell selection
Solution Approach 1:
The patent enables UEs to perform preliminary actions by collecting and sharing service information (traffic load, QoS metrics) before handover decisions are made. Managing UEs aggregate this information in advance, allowing peer UEs to predict QoS conditions of target cells and select optimal handover targets proactively, avoiding service interruptions caused by reactive handover based solely on signal strength.
3Measurement precision
If peer UE service information is shared extensively, then QoS prediction accuracy is improved, but power consumption increases due to additional processing and communication
Solution Approach 1:
The patent implements a self-service architecture where managing UEs autonomously collect, aggregate, and manage service information without requiring continuous network intervention. Peer UEs query managing UEs for pre-aggregated information rather than continuously transmitting their own measurements, reducing individual UE processing and communication overhead while maintaining accurate QoS predictions through shared collective intelligence.
4Loss of information
If network signaling is reduced for handover decisions, then signaling overhead is decreased, but the ability to ensure QoS deteriorates due to lack of centralized coordination
Solution Approach 1:
The patent extracts the information aggregation and QoS prediction function from the network core and relocates it to managing UEs at the edge. This extraction allows the network to reduce signaling overhead for handover decisions while maintaining QoS guarantees through distributed intelligence. The managing UEs locally aggregate service information and provide predictions to peer UEs, eliminating the need for continuous network-mediated information exchange while preserving centralized coordination benefits.
Data Source
AI summary
The present application relates to devices and components including apparatus, systems, and methods to provide and/or implement user equipment-centric predictive mobility with subnetwork support in wireless communication systems.