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H.265/HEVC video transmission over 4G cellular networks Jassal, Aman
Abstract
Long Term Evolution has been standardized by the 3GPP consortium since 2008, with 3GPP Release 12 being the latest iteration of LTE Advanced, which was finalized in March 2015. High Efficiency Video Coding has been standardized by the Moving Picture Experts Group since 2012 and is the video compression technology targeted to deliver High-Definition video content to users. With video traffic projected to represent the lion's share of mobile data traffic in the next few years, providing video and non-video users with high Quality of Experience is key to designing 4G systems and future 5G systems. In this thesis, we present a cross-layer scheduling framework which delivers video content to video users by exploiting encoding features used by the High Efficiency Video Coding standard such as coding structures and motion compensated prediction. We determine which frames are referenced the most within the coded video bitstream to determine which frames have higher utility for the High Efficiency Video Coding decoder located at the user's device and evaluate the performances of best effort and video users in 4G networks using finite buffer traffic models. We look into throughput performance for best effort users and packet loss performance for video users to assess Quality of Experience. Our results demonstrate that there is significant potential to improve the Quality of Experience of best effort and video users using our proposed Frame Reference Aware Proportional Fair scheme compared to the baseline Proportional Fair scheme.
Item Metadata
Title |
H.265/HEVC video transmission over 4G cellular networks
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Creator | |
Publisher |
University of British Columbia
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Date Issued |
2016
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Description |
Long Term Evolution has been standardized by the 3GPP consortium since 2008, with 3GPP Release 12 being the latest iteration of LTE Advanced, which was finalized in March 2015. High Efficiency Video Coding has been standardized by the Moving Picture Experts Group since 2012 and is the video compression technology targeted to deliver High-Definition video content to users. With video traffic projected to represent the lion's share of mobile data traffic in the next few years, providing video and non-video users with high Quality of Experience is key to designing 4G systems and future 5G systems.
In this thesis, we present a cross-layer scheduling framework which delivers video content to video users by exploiting encoding features used by the High Efficiency Video Coding standard such as coding structures and motion compensated prediction. We determine which frames are referenced the most within the coded video bitstream to determine which frames have higher utility for the High Efficiency Video Coding decoder located at the user's device and evaluate the performances of best effort and video users in 4G networks using finite buffer traffic models. We look into throughput performance for best effort users and packet loss performance for video users to assess Quality of Experience. Our results demonstrate that there is significant potential to improve the Quality of Experience of best effort and video users using our proposed Frame Reference Aware Proportional Fair scheme compared to the baseline Proportional Fair scheme.
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Genre | |
Type | |
Language |
eng
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Date Available |
2016-02-02
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Provider |
Vancouver : University of British Columbia Library
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Rights |
Attribution-NonCommercial-NoDerivs 2.5 Canada
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DOI |
10.14288/1.0223893
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URI | |
Degree | |
Program | |
Affiliation | |
Degree Grantor |
University of British Columbia
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Graduation Date |
2016-05
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Campus | |
Scholarly Level |
Graduate
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Rights URI | |
Aggregated Source Repository |
DSpace
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Item Media
Item Citations and Data
Rights
Attribution-NonCommercial-NoDerivs 2.5 Canada