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VSQIinstant values are calculated per sec to easily detect and reflect the real time network quality and its impact on video streaming. Therefore, VSQIinstant is defined by:
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Where:
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where (i, x) variables pair can be (resolution r, resolution value x) and (framerate fr, framerate value x)
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As can be seen in equation (1), VSQI dependency on the resolution and frame rate parameters is described by a sigmoid function. The sigmoidal (“S” shape) has been selected because it is well known that human perception shows this behavior in relationship to individual video quality parameters. In addition, extensive testing and analysis showed the multiplicative effect of individual video quality parameters on the video quality. VSQIsession values are calculated per video streaming session (one value after the first 30sec video streaming time) and they capture the long-term effects of video playout interruption (rebufferings) as well as possible resolution changes. VSQIsession is based on all the VSQIinstant values during the first 30-second video streaming time weighted by the video interruption periods.
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Where the weighting function W depends on rebuffering parameters which can be length, percentage or count.
Generic for mobile OTT applications VSQI works for any OTT video streaming application running on devices with displays of 6” and 7’’. However, VSQI values are unique per application, and video quality results on different OTT applications cannot be compared to each other. Trusting VSQI performance VSQI training and tuning is based on a large set of simulated network conditions containing error patterns, including delay, jitter and latency, which are characteristic to 4G and 5G NR networks. VSQI performance has been tested on real-life network conditions showing from poor to very good quality. This means both the VSQI accuracy and robustness are fully tested. As mentioned above, MOS target values against which VSQI has been tested are based on the ITU-T P.1203-4.x series. The performance results are presented in Figure 3. VSQIsession and MOS target values for a wide range of conditions and quality are compared after applying a 3rd-order polynomial mapping between the two data sets to remove any bias, as required by ITU-T P.1401 (Statistical evaluation of QoE models). The correlation coefficient, RMSE (Root Mean Square Error) and MAE (Mean Absolute Error) as defined by ITU-T P.1401 are calculated and all the performance statistics show values within the performance requirements on QoE video models (ITU-T P.1203-1204.x series), such as R>80%, RMSE and MAE<0.5 The regression chart is presented in Figure 3a. These results prove VSQI trustful performance, reflected by the fact that although designed to only quantify the network’s impact, VSQI provides high accuracy on the MOS scale, like a full QoE video quality model. A full QoE model reflects the impact of all components affecting video quality: network, video content, OTT application and device performance. This is largely expected since the network weighs in most on the quality, as described in section “ A pragmatic testing solution ”.
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