Abstract
Long Term Evolution (LTE) has been standardized by the 3GPP consortium since 2008 in 3GPP Release 8, with 3GPP Release 12 being the latest iteration of LTE Advanced (LTE-A), which was finalized in March 2015. High Efficiency Video Coding (H.265) has been standardized by MPEG since 2012 and is the Video Compression technology targeted to deliver High-Definition (HD) and Ultra High-Definition (UHD) Video Content to users. With video traffic projected to represent the lion's share of mobile data traffic, providing users with high Quality of Experience (QoE) is key to designing 4G systems and future 5G systems. In this paper, we present a cross-layer scheduling framework which delivers frames to unicast video users by exploiting the encoding features of H.265. We extract information on frame references within the coded video bitstream to determine which frames have higher utility for the H.265 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. Our results demonstrate that there is significant potential to improve the QoE of all users compared to the baseline Proportional Fair method by adding media-awareness in the scheduling entity at the Medium Access Control (MAC) layer of a Radio Access Network (RAN).
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