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Wi-Fi User's Video QoE in the Presence of Duty Cycled LTE-U

Authors:

Mohit Kumar Singh,

Anand M. Baswade,

Antony Franklin A,

Bheemarjuna Reddy TammaAuthors Info & Claims

MobiCom '18: Proceedings of the 24th Annual International Conference on Mobile Computing and Networking

Pages 720 - 722

https://doi.org/10.1145/3241539.3267780

Published: 15 October 2018 Publication History

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Abstract

Recent advances in LTE operating in unlicensed spectrum (LTE-U) has grabbed a lot of attention from industry and academia. The duty cycled LTE-U is shown to be fair with Wi-Fi technology by following an ON-OFF cycle for its transmission. However, the effect of LTE-U on the video quality of Wi-Fi users has not been studied in the literature. In this work, we study the video quality performance of a Wi-Fi user in the presence of LTE-U, in a testbed system. Our results show that the parameters that contribute to the video QoE (Quality of Experience) of Wi-Fi users get adversely affected as the fraction of channel utilized by LTE-U increases, but the same is not shown to be true with another Wi-Fi. We found that poor video QoE of Wi-Fi users in the presence of LTE-U is because of a large number of packet collisions and less channel access time due to ON cycle of LTE-U.

References

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Yao Liu et al. 2015. Deriving and Validating User Experience Model for DASH Video Streaming . IEEE Transactions on Broadcasting, Vol. 61, 4 (2015), 651--665.

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Christopher Mueller et al. 2013. Dynamic Adaptive Streaming over HTTP/2.0. In IEEE ICME.

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Dziedzic ASathya VRochman MGhosh MKrishnan S(2020)Machine Learning Enabled Spectrum Sharing in Dense LTE-U/Wi-Fi Coexistence ScenariosIEEE Open Journal of Vehicular Technology10.1109/OJVT.2020.29815191(173-189)Online publication date: 2020
https://doi.org/10.1109/OJVT.2020.2981519

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Information

Published In

MobiCom '18: Proceedings of the 24th Annual International Conference on Mobile Computing and Networking

October 2018

884 pages

ISBN:9781450359030

DOI:10.1145/3241539

General Chairs:
Rajeev Shorey
TCS Innovation Labs, India
,
Rohan Murty
Soroco, USA/India
,
Program Chairs:
Yingying (Jennifer) Chen
WINLAB, Rutgers University, USA
,
Kyle Jamieson
Princeton University, USA

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 15 October 2018

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Funding Sources

Meity Govt. of India

Conference

MobiCom '18

Sponsor:

SIGMOBILE

MobiCom '18: The 24th Annual International Conference on Mobile Computing and Networking

October 29 - November 2, 2018

New Delhi, India

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MobiCom '18 Paper Acceptance Rate 42 of 187 submissions, 22%;

Overall Acceptance Rate 440 of 2,972 submissions, 15%

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Cited By

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Dziedzic ASathya VRochman MGhosh MKrishnan S(2020)Machine Learning Enabled Spectrum Sharing in Dense LTE-U/Wi-Fi Coexistence ScenariosIEEE Open Journal of Vehicular Technology10.1109/OJVT.2020.29815191(173-189)Online publication date: 2020
https://doi.org/10.1109/OJVT.2020.2981519

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