Bandwidth allocation for video delivery in wireless networks with QoE constraints for spatially random user population

Abstract

As video streaming becomes one of the most fast growing and dominant applications in fixed and mobile networks, how to provide high quality and user satisfaction is a widely studied research topic. In this paper, we develop an analytical framework to derive the downloading rate and bandwidth requirement, so that certain objective quality of experience (QoE) constraints are met. Particularly, applicationspecific key performance indicators (KPIs) such as start-up delay and starvation probability are taken into account. Our analysis addresses heterogeneity of both user spatial locations and video requests. Computer simulations are conducted to verify the accuracy of the proposed analytical framework. Based on the analytical framework, a media server can adapt the downloading rate allocation, e.g., relative to the video playback rate, depending on user demands and network conditions. Index Terms-Video streaming, QoE, starvation probability, pre-fetching threshold, download-to-playback rate ratio.

Efficient Adaptive Intra Refresh Error Resilience for 3D Video Communication

“…The creditable performance of the H.264/AVC has improved users quality of experience (QoE) meeting by meeting viewers 'expectation, feelings, and thoughts of 3D video. However, the predictive nature of the multi-view video coding (MVC) makes the compressed bitstreams vulnerable lens to burst and random bit-errors often leave users in need of efficient QoE [11][12][13][14][15].In addition, father and child family chain of relationship that exists in the hierarchical B picture representation of the group of picture (GOP) in video compression causes distortion. The effect of this distortion in a variable length codes (VLC) may result to loss of synchronisation between the decoder and encoder.…”