QMC

QoE Measurement Collection

Services
Introduced in Rel-14
QMC is a framework for collecting Quality of Experience (QoE) measurements from user equipment (UE) in 3GPP networks. It enables operators to gather subjective and objective data on user-perceived service quality, such as video streaming performance. This data is crucial for network optimization, service assurance, and improving customer satisfaction.

Description

QoE Measurement Collection (QMC) is a standardized framework within 3GPP for the collection of Quality of Experience (QoE) metrics from end-user devices. QoE differs from traditional Quality of Service (QoS) by focusing on the subjective perception of a service by the end-user, such as video quality, audio clarity, or application responsiveness. The QMC framework defines the procedures, signaling, and information models necessary for the network to configure, activate, and receive QoE measurements from the User Equipment (UE). It operates across multiple service types, with a primary focus on media streaming services like HTTP Adaptive Streaming (HAS).

The architecture involves several network functions. The Policy Control Function (PCF) or Application Function (AF) can request QoE measurements for specific users or services. This request is communicated to the UE via the Access and Mobility Management Function (AMF) and the Radio Access Network (RAN). The UE, equipped with a QoE measurement client, then performs the measurements according to the received configuration. This configuration includes parameters like the service type (e.g., video streaming), target metrics (e.g., initial playback delay, rebuffering ratio, video codec information), and reporting triggers (e.g., periodic, event-based).

The UE collects data during the service session. For video streaming, this can include application-layer metrics like buffer status, resolution changes, and stall events. Once collected, the measurement reports are sent back to a designated collection entity, often a Mediation Function (MF) or directly to an Application Function (AF) like a video analytics server. The reports are transported over standardized interfaces, such as Nq between the UE and the AMF, and potentially Nm between the AMF and the MF. The collected data is then aggregated and analyzed by the operator or service provider to gain insights into real-world service performance, identify problem areas, and drive network and service improvements.

Purpose & Motivation

QMC was introduced to address the growing need for operators and service providers to understand the actual end-user experience, which is not fully captured by traditional network-centric QoS metrics. As services like video streaming became dominant, issues like video stalling, resolution degradation, and slow start-up times directly impacted user satisfaction and retention. Prior to QMC, operators relied on network probes, deep packet inspection (DPI), or limited, proprietary device reporting, which provided an incomplete or indirect view of QoE.

The creation of QMC was motivated by the industry's shift towards user-centric network management. It solves the problem of obtaining direct, standardized, and rich QoE data from the endpoint itself—the UE. This enables correlation of network conditions (e.g., radio signal strength, throughput) with actual application performance as perceived by the user. By standardizing this collection framework in Rel-14 and beyond, 3GPP ensured interoperability between devices and network analytics platforms, allowing for scalable, automated QoE-driven optimization and closed-loop operations.

Key Features

  • Standardized configuration of QoE measurements from the network to the UE
  • Support for multiple service types, primarily focusing on media streaming (e.g., DASH)
  • Collection of application-layer metrics like playback events, buffer levels, and codec information
  • Flexible reporting triggers including periodic reporting and event-triggered reporting
  • Transport of measurement reports via core network interfaces (e.g., Nq, Nm)
  • Integration with policy control (PCF) and application functions (AF) for targeted measurement campaigns

Evolution Across Releases

Rel-14 Initial

Introduced the foundational QMC framework for LTE/EPC networks. Defined the initial architecture, signaling procedures (via PCRF and eNB), and QoE measurement configuration for HTTP Adaptive Streaming services. Established basic reporting mechanisms from UE to a collection function.

Enhanced QMC for 5G System (5GS) integration. Aligned the framework with 5G core network functions, introducing support for service-based interfaces and integration with the PCF and NEF. Expanded measurement configuration transport via the AMF.

Introduced support for additional media types and enhanced measurement parameters. Added capabilities for QoE measurement collection in edge computing (MEC) scenarios and improved reporting efficiency.

Further expanded service coverage and refined procedures. Added support for new application types and enhanced the alignment with network analytics and automation use cases.

Continued enhancements for advanced services and integration with network slicing. Focused on improving scalability and the granularity of QoE data collection for differentiated services.

Ongoing evolution with potential updates for new media codecs, immersive services, and tighter integration with AI/ML-driven network optimization.

Expected to include further refinements and support for emerging service paradigms, maintaining QMC as a key enabler for experience-driven network management.

Defining Specifications

SpecificationTitle
TS 23.501 3GPP TS 23.501
TS 26.114 3GPP TS 26.114
TS 26.247 3GPP TS 26.247
TS 26.567 3GPP TS 26.567
TS 26.812 3GPP TS 26.812
TS 26.942 3GPP TS 26.942
TS 28.308 3GPP TS 28.308
TS 28.405 3GPP TS 28.405
TS 28.406 3GPP TS 28.406
TS 32.101 3GPP TR 32.101
TS 36.413 3GPP TR 36.413
TS 36.423 3GPP TR 36.423
TS 37.340 3GPP TR 37.340
TS 38.300 3GPP TR 38.300
TS 38.410 3GPP TR 38.410
TS 38.413 3GPP TR 38.413
TS 38.420 3GPP TR 38.420
TS 38.470 3GPP TR 38.470
TS 38.473 3GPP TR 38.473
TS 38.890 3GPP TR 38.890