In part one of this blog series, we established that an expanded test methodology with new test cases is required to characterize the quality of experience (QoE) of 5G networks. Let’s now take a closer look at how to define and set up QoE test cases for these new “user” experiences. First, we need to understand the requirements of the specific use case that define the factors and weightings that constitute QoE of the connected thing or device.
Without knowing the underlying service and device requirements, network quality engineers do not know what aspects and metrics should be treated as important key performance indicators (KPI). So we need to compile the set of parameters and KPIs, and define thresholds, creating good/bad KPI limits for each application and use case. This is still at a very early stage, but one approach would be to start at the PHY and logical layers and work up to the apps and use case, defining what needs to be measured.
One positive aspect is that this sort of understanding of use case QoE can drive the Network Operations Center (NOC) to Service Operations Center (SOC) transformation that operators are making. The SOC is important because it is via this service-driven environment that operators hope to differentiate their customer experiences. For example, a car manufacturer can understand which operators’ network is best suited for its connected or autonomous cars. So we can see that active testing and understanding of QoE per use case, allied to network operations, will be a key enabler of future 5G business cases.
Implications for test solution vendors
As with operators’ challenge mentioned in part 1 of this series, test equipment vendors must produce solutions that can measure multiple virtual networks at the same time and the same location with different methodologies.
An examination of the metrics required to characterize 5G uses cases quickly reveals that measuring QoE becomes more complex and more demanding in terms of the data acquisition of additional measurement parameters with greater precision in the RAN. This also drives the need to provide post-processing analytics that encompasses new models for quality of service (QoS) and QoE measurements for network benchmarking, optimization and monitoring.
The consequences of degradation or loss of service for some mission-critical 5G use cases go way beyond an unsatisfactory voice call to a friend or a YouTube video freezing when you stream it on your phone. The critical nature of some applications demands that test solutions must be independent, transparent and traceable to certified international standards and not aligned to proprietary techniques or individual network equipment vendors.
Testing 5G QoE
5G introduces a new dimension and type of use cases; not only the physical test equipment required to sample the network, e.g., a wider bandwidth scanner, but also the methodology of what parameters to test for a specific application and how to post-process the data. There will be new KPIs that contribute to the evaluation of QoS and other factors that feed into QoE. QoE can be built up from the lower layers and use a model to define how QoS maps into QoE.
The key question is what does good QoE look like for a sensor in an industrial IoT deployment, or a connected car, or a VR device, or any specific 5G use case? In these use cases, we need to have a way of understanding whether QoE is good or bad and what the thresholds are. For a simple example, take call setup time. What is an acceptable “setup time” for a sensor alarm, or an autonomous car, or in remote medical use cases?
What is an acceptable “setup time” for a sensor alarm?
What may have been well defined in previous use cases, for example, a subscriber streaming a movie on their smartphone, may well not be transferable to 5G use cases. Attention will have to be given to the range of acceptable values of QoE for each specific application, below which it becomes a problem and above which it brings no additional value.
Therefore, it is apparent that testing 5G QoE, particularly for applications other than enhanced Mobile Broadband (eMBB), will require more metrics to be acquired with greater precision that will need to be post-processed more quickly and with greater complexity.
In the final part of this series about testing 5G QoE, we will examine the role of standards organizations and the approach adopted by Rohde & Schwarz to tackle the 5G QoE measurement challenge.
Further information on testing 5G networks can be found via the following link: www.rohde-schwarz.com/mnt-5g