Moving beyond traditional network KPIs
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Operators are increasingly focused on enhancing end users’ QoE in order to increase
their revenue, yet challenges still remain. For example, how can they measure user
experience of different services and thus realize QoE-oriented network management?
Traditional network KPIs as basis of QoE are not perfect
Mobile networks are trending toward IP following a booming growth in services;
besides traditional voice and SMS, other services and applications like web browsing
and streaming media are also using the mobile broadband pipe. Richer services, higher
quality, and enhanced QoE are becoming the key to running a profitable business.
Higher service quality helps retain existing users and win new ones, while degraded
service quality is directly linked to increased churn rate and a poor brand image.
Service quality has become the core competitiveness of any operator. To improve user
experience, operators need to manage service quality in real time and optimize it to
attract and retain users. In addition, active prevention is required to guard against any
potential fault.
Operation and maintenance (O&M) based on traditional KPIs can hardly meet
operators’ QoE management needs. In most cases, user complaints are mainly related
to poor voice quality, noise, and one-way audio, while traditional network management
system (NMS), which only measures KPIs like signaling connection rate and call drop
rate, lacks measurement on voice quality indicators to help identify the causes of user
complaints.
There are two challenges to network quality management due to the increasing quality
demand and complexity of diversified services in MBB and IP transformation: First,
the KPIs are measuring network quality on network level instead of service application
level or user level, lacking the indicators to monitor voice communications quality in an
end-to-end (E2E) manner. As a result, the user QoE is inconsistent with the KPI
performance. Second, the NMS uses a macro approach to collect data, which is too
broad to reflect the QoE quickly and correctly based on the actual network
performance.
With more comprehensive, measurable and visualized indicators, operators can
promptly spot the QoE gap for services across different periods and networks, and
optimize their performance accordingly.
Establishing an improved QoE evaluation system
Involving complex psychological and physiological factors, QoE refers to an end user’s
satisfaction level when it comes to a service provider or specific network performance.
Factors affecting QoE can be divided into non-technical factors and technical factors.
Non-technical factors are mainly associated with the policies and services provided by
operators; while technical factors are closely related to networks and terminals – they
are the cornerstone when it comes to user satisfaction and a critical element in the key
quality indicator (KQI) system.
Currently, there are no unified criteria to measure QoE in the industry. Through
in-depth research and based on its rich experience in network and service O&M,
Huawei has rolled out a QoE evaluation system. Incorporating the research of TMS,
ETSI and 3GPP, the system consists of a series of objective and measurable QoE, KQI
and KPI.
Perceived E2E user experience: Huawei’s QoE evolution system is user-oriented
and based on actual service scenarios. By analyzing service features, application
scenarios and the network elements and processes involved, the system can detect the
key factors that impact QoE and facilitate troubleshooting. The indicators selected are
comprehensive and can reflect the QoE features independently and effectively. As a
result, the indicators remain consistent with real user experience.
Real-time QoE monitoring and measurement: Indicators in the QoE evolution
system have clearly defined the meanings, objectives and measurement methods, which
simplifies the processes of verifying QoE for each service in the network. Operators
can ensure service quality and QoE based on a unified O&M platform. Obtaining data
through the NMS and probes, the QoE evaluation system can monitor indicators
classified by user groups, users, regions, holidays, and specific days. In this context, the
service quality and QoE are clearly stated, while potential networks faults are detected.
QoE, KQI, and KPI evaluation model: To enable fast troubleshooting, the system
adopts an evaluation model which correlates QoE, KQI and KPI. By referring to the
TMF GB923, Huawei has established a correlation model for each service, which
covers factors like QoE, service KQI and network KPI. By clearly indentifying the
relationships among those three factors, the model helps enhance service and network
quality, while enabling fast troubleshooting of user complaints. In addition, the model
helps locate service faults in an E2E manner, thanks to its capability to trace and
analyze the whole service transaction, i.e. from the first flow message to the last.
Huawei’s QoE evaluation system has been adopted and well-received by operators. For
example, China Mobile teamed up with Huawei and launched the QoE evaluation
system to optimize its voice service quality. Covering the establishment of service KQI,
network KPI, and equipment performance indicators, the system enhances the service
quality monitoring methodology on voice services in terms of E2E completion rate, call
duration, and call drop rate. In addition, new indicators were integrated to extend China
Mobile’s monitoring system to cover the QoE domain, such as voice quality, one-way
audio, crosstalk, and echo. This helps monitor in real time the network performance and
troubleshoot accordingly.
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