5G Connectivity Loss Data Collection Across WLAN and PC5
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Solution Overview
Problem
Existing MDT data collection methods in 5G networks fail to accurately reflect user experience in mixed connectivity scenarios, as they only consider radio signal loss and do not account for alternative network connections such as WLAN or PC5, leading to underestimation of service availability and inability to identify real connectivity interruptions.
Innovation Solution
Introduce a new 'Out of Any Connectivity' state in UEs to monitor and log loss of any available network connection, including Wi-Fi, PC5, and satellite signals, enabling differentiated data collection and reporting through extended MDT configurations and triggers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If MDT data collection only monitors radio signal loss, then the measurement system remains simple, but the accuracy of service availability detection deteriorates in mixed connectivity scenarios
Solution Approach 1:
The patent segments the connectivity monitoring function into separate components for different network types (radio network monitoring, WLAN monitoring, V2X monitoring). Each component independently monitors its specific network interface, and the system integrates their states to determine overall service availability. This segmentation allows accurate detection across mixed connectivity scenarios while keeping each monitoring component relatively simple.
Solution Approach 2:
The patent implements a universal connectivity monitoring mechanism that can handle multiple network types (radio, WLAN, V2X) through a unified framework. The MDT data collection system is extended to monitor and report service availability across different connectivity interfaces using a common measurement and reporting structure, enabling accurate service availability detection without requiring separate complex systems for each network type.
2Reliability
If MDT data collection monitors multiple network interfaces, then the accuracy of connectivity interruption detection improves, but the device complexity increases
Solution Approach 1:
The patent divides the monitoring task into separate modules for each network interface (radio interface monitoring, WLAN interface monitoring, PC5 interface monitoring). Each module independently tracks its respective interface state, and the system combines these individual states to determine overall connectivity status. This segmentation improves detection reliability by ensuring each interface is monitored by specialized logic while avoiding the complexity of a monolithic monitoring system.
Solution Approach 2:
The patent implements feedback mechanisms where each network interface monitoring component continuously reports its state (connected/disconnected) to a central determination module. This feedback loop enables the system to accurately track connectivity changes across multiple interfaces and reliably identify when all interfaces are simultaneously disconnected, improving detection reliability through continuous state updates.
3Ease of manufacture
If existing MDT methods are used in mixed connectivity scenarios, then the implementation remains simple, but the feedback on real user experience becomes inaccurate
Solution Approach 1:
The patent configures the UE to perform preliminary actions by establishing monitoring of multiple network interfaces before connectivity interruptions occur. The system proactively sets up measurement configurations for radio, WLAN, and V2X interfaces, enabling it to capture accurate service availability data when interruptions happen. This preliminary preparation ensures real user experience information is captured without requiring complex post-processing or additional infrastructure.
Solution Approach 2:
The patent enables the UE to self-service by autonomously monitoring its own connectivity state across multiple interfaces and generating MDT reports based on its observed service availability. The device independently determines when it is disconnected from all networks and reports this information without requiring external verification or complex network-side processing, maintaining implementation simplicity while capturing accurate user experience data.
Data Source
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AI summary
A first method includes receiving, while in 5G-network coverage, logged measurement configuration from a network node for use during a loss of 5G-network coverage; determining connectivity over at least one non-5G-network service; when connectivity over the non-5G-network service is detected, storing "Out of 5G Radio Coverage" information; and, when 5G-network coverage is detected, resuming monitoring 5G-network coverage. A second method includes receiving, while in 5G- network coverage, a logged measurement configuration from a network node for use during a loss of 5G-network coverage; determining connectivity over at least one non-5G- network service; when connectivity over the at least one non-5G-network service is not detected, entering an "Out of Any Connectivity" state; logging "Out of Any Connectivity" data; storing the "Out of Any Connectivity" data; when 5G-network coverage is detected, exiting from the "Out of Any Connectivity" state; reporting availability of logged "Out of Any Connectivity" data to the network node; and forwarding the logged "Out of Any Connectivity" data to the network node.