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Calibration to MOS The VSQI model aims to describe in a single number the video streaming quality as perceived by users during playback. Therefore, the VSQI model is based on mapping the model’s input parameters to MOS target values for a broad range of 4G and 5G network conditions. The reference data source for the MOS target values was generated based on ITU-T P.1203- 1204 series and ITU-T TR PSTR-PXNR - No-reference pixel-based video quality estimation algorithm , 2019. Support of UHD video VSQI values rank on the whole MOS scale for a large range of frame rates and resolutions up to 8K resolution. Video content dependency Video quality is highly dependent on the video content type, including its complexity, density and dynamicity. More intense video content with increased complexity/density/dynamicity is more sensitive to network errors. This means that it is more challenging for codecs and for the network, with the consequence that the human vision perceives degradations produced by network errors more easily than if the same type and level of degradations impacted less intense video content. An example of the perceived video quality (MOS) on content dependency at various resolutions is presented in Figure 3.
It should be noted that the encryption level can determine the number of KPIs available for measurement. Therefore, it is understood and agreed within ETSI that depending on the OTT application, the set of KPIs available can become limited. In addition, depending on the level of encryption, information regarding the application’s configuration can be available (Table 2). Video Streaming Quality Index (VSQI) As discussed above, ETSI defines a set of KPIs for describing the video quality during presentation (playback) as perceived by users. Even though this KPI set is valuable for troubleshooting and optimization, ETSI does not provide a single number (score) which can describe the overall playback video quality expressed MOS (Mean Opinion Score). ITU-T SG12 provides a series of models, but as of today none are suitable for today’s native OTT application testing on devices in drive test scenarios. Infovista Network Testing has developed a model which aims to provide a video streaming quality index expressed in QoE terms (MOS), suitable for any on- device OTT application and meaningful for network- centric troubleshooting and optimization based on drive test data 3 . The evolved VSQI model’s design considers various aspects related to its scope as a testing solution for today’s OTT application testing solution implemented in drive testing tools. Input parameters The model relies on the fact, proven by extensive testing and analysis, that there are three main factors rooted in the network which impact video streaming quality during playback: resolution, frame rate and interruptions/buffering (Table 1). The resolution and frame rate are determined by the dynamically available bandwidth changes and possible limitations caused by either network congestion and/or radio link RF quality. The video interruptions/buffering is caused by extended network delay/jitter and/or loss. Therefore, the model’s input parameters are resolution, frame rate and playout state, including initial buffering, re-buffering and playing.
3. This model has been developed based on previous work described in Ascom Network Testing: Video Streaming Quality Measurement with VSQI. Technical Paper , 2009; Ascom Network Testing: Evaluating Mobile Video Service Quality with Ascom TEMS , 2011.
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