Quality of Experience Oriented Adaptive Video Streaming for Edge Assisted Cellular Networks

Abstract

HTTP adaptive streaming accounts for a large part of mobile Internet traffic. With the developing cellular communication technologies, the standard dynamic adaptive streaming over HTTP technique allows mobile terminals to adaptively configure the transmission rate of video streaming applications and achieve high quality of experiences (QoE) with many adaptive bitrate algorithms. However, existing schemes either neglect to consider radio access network (RAN) side conditions or only consider simple RAN information optimization schemes. In this letter, we propose a QoE-oriented adaptive video streaming scheme based on a dueling deep Q-learning network. The proposed scheme improves the QoE by jointly considering the physical layer transmission bandwidth and the higher layer buffer status. Through the numerical and prototyping results, we show that our proposed scheme outperforms the existing schemes, with the average QoE improvements of 12.6% to 28.8%.