UE QoE Incident Reporting with Severity and Radio Measurements
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Solution Overview
Problem
Existing QoE measurement techniques in 5G networks are complex, resource-intensive, and lack real-time accuracy due to increased traffic and encryption, while service provider metrics are non-transparent and require multiple agreements, making them unfeasible for precise user experience estimation.
Innovation Solution
UEs report QoE incident reports with severity categories and radio measurements to RAN nodes, which are then processed by NNFs to compute KPIs and identify underlying issues, eliminating the need for service provider agreements and reducing resource intensity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If user-plane probes are installed to monitor subscriber traffic and derive QoE KPIs, then measurement precision is improved, but device complexity and resource consumption increase significantly
Solution Approach 1:
The UE performs self-measurement of QoE parameters using application layer measurements and reports them directly to the network. This eliminates the need for complex external probing infrastructure while maintaining measurement accuracy, as the device itself generates the measurement data rather than requiring external probes to collect it.
Solution Approach 2:
The patent extracts only the essential QoE measurement functionality from complex probing systems by having the UE independently perform measurements and report results. This removes the need for heavy analytics platforms and machine learning models while retaining the core capability to measure and report QoE parameters.
2Measurement precision
If user-plane probes collect and correlate network events with end-to-end service quality metrics, then measurement precision is improved, but use of energy increases due to resource-intensive processing
Solution Approach 1:
The UE independently performs QoE measurements and generates reports without requiring energy-intensive external probing and correlation systems. The device uses its own application layer measurements and radio layer measurements to derive QoE parameters, eliminating the need for complex energy-consuming analytics processing.
Solution Approach 2:
The patent performs only the essential measurements needed for QoE assessment at the UE level, rather than collecting and correlating all possible network events. This partial action approach reduces processing requirements and energy consumption while still achieving accurate QoE measurement for the specific parameters of interest.
3Measurement precision
If service provider metrics are collected through multiple agreements, then measurement precision is improved, but ease of operation deteriorates due to complex coordination requirements
Solution Approach 1:
The UE autonomously generates QoE measurement reports using its own measurements without requiring agreements with multiple service providers. The device independently collects application layer and radio layer data, processes it, and reports results directly to the network, eliminating complex coordination and agreement processes.
Solution Approach 2:
The patent creates a universal QoE measurement mechanism that works across different service providers and network configurations without requiring specific agreements. The UE's self-measurement capability is provider-agnostic and can be deployed universally, making the system easy to operate and deploy.
4Measurement precision
If advanced analytics systems collect and correlate elementary network events, then measurement precision is improved, but device complexity increases due to big data analytics platforms
Solution Approach 1:
The patent extracts only the essential measurement functionality from complex analytics systems by having the UE perform measurements locally and report results. This removes the need for big data analytics platforms while retaining the ability to measure QoE parameters accurately for the specific metrics that matter.
Solution Approach 2:
The UE independently performs QoE measurements and generates reports without requiring external analytics platforms. The device uses its own measurement capabilities to derive QoE parameters from application layer and radio layer data, eliminating the need for complex external processing systems.
Data Source
AI summary
Embodiments include methods for a user equipment (UE) configured to report quality of experience (QoE) measurements in a radio access network (RAN). Such methods include monitoring performance of one or more services, of a UE application layer, that communicate with corresponding one or more application servers via the RAN. Such methods include, based on the monitoring, detecting one or more incidents that negatively affect user QoE and classifying each of the incidents as one of a plurality of categories of severity. Such methods include sending to a RAN node a message that includes the following: a QoE incident report that includes at least one count of incidents during a measurement period, with each count corresponding to a different category of severity; and results of radio measurements performed by a UE radio layer during the measurement period. Other embodiments include complementary methods for a network node or function (NNF).