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C. Midoglu, P. Svoboda, M. Rupp:
"Modeling Indoor WLAN Performance Towards User-Oriented Evaluation Metrics";
in: "Telecommunications Forum Telfor (TELFOR), 2015 23rd", IEEE Communications Society, 2015, ISBN: 978-1-5090-0054-8, S. 83 - 86.

Large scale Wireless Local Area Network (WLAN) deployment in the recent years, along with a significant increase in mobile data traffic has created a need for better understanding, modeling and ultimately optimizing WLAN performance. Studies show that most mobile data usage takes place in indoor environments such as homes and offices, and this has brought industry and academia together in the particularly challenging topic of WLAN performance modeling for indoors. With the IEEE802.11ax High Efficiency WLAN (HEW) standard soon to be rolled out, great emphasis is also put on estimating performance in relation to Quality of Experience (QoE) for different user profiles. In this paper, we provide a simple model of indoor WLAN performance in terms of key metrics such as coverage and data rate, considering propagation modeling, building layout and penetration loss. We demonstrate how the model can estimate user experience in different types of flats and give an example QoE translation for perceived video quality using Peak Signal-to-Noise Ratio (PSNR) and Mean Opinion Score (MOS).

Large scale Wireless Local Area Network (WLAN) deployment in the recent years, along with a significant increase in mobile data traffic has created a need for better understanding, modeling and ultimately optimizing WLAN performance. Studies show that most mobile data usage takes place in indoor environments such as homes and offices, and this has brought industry and academia together in the particularly challenging topic of WLAN performance modeling for indoors. With the IEEE802.11ax High Efficiency WLAN (HEW) standard soon to be rolled out, great emphasis is also put on estimating performance in relation to Quality of Experience (QoE) for different user profiles. In this paper, we provide a simple model of indoor WLAN performance in terms of key metrics such as coverage and data rate, considering propagation modeling, building layout and penetration loss. We demonstrate how the model can estimate user experience in different types of flats and give an example QoE translation for perceived video quality using Peak Signal-to-Noise Ratio (PSNR) and Mean Opinion Score (MOS).

WLAN, IEEE 802.11ax, HEW, performance, indoor, QoE, PSNR, MOS

http://dx.doi.org/10.1109/TELFOR.2015.7377419