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’sQoE 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’sQoE 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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