A Joint Rate and Buffer Control Scheme for Video Transmission over LTE Wireless Networks

In wireless communication systems, the quality of time-varying wireless channels and limited resources, make video transmission very challenging. In order to play video frequently, this paper proposes a novel method of QoE (Quality of Experience)-aware video transmission optimization algorithm over LTE networks by jointly controlling the transmission rate and playback buffer management to reduce the probability of video playback interruptions and adapt to constantly changing network status effectively. In order to calculate QoE more accurately and meet user’s requirements, this paper also proposes an improved QoE calculation model based on ITU-TP.1201, which considers video bitrate, playback interruption duration, number of playback interruptions, buffer overflow duration, and number of buffer overflows. The experimental results demonstrate that the proposed method can reduce the probability of video playback interruptions and video frame skipping under the finite resource constraints and varying network status more effectively compared with an existing algorithm, thus improving the QoE of video streaming.

[1]  Guizhong Liu,et al.  Quality-Driven Cross-Layer Design for H.264/AVC Video Transmission over OFDMA System , 2014, IEEE Transactions on Wireless Communications.

[2]  Abdulmotaleb El-Saddik,et al.  Toward a Mathematical Model for Quality of Experience Evaluation of Haptic Applications , 2013, IEEE Transactions on Instrumentation and Measurement.

[3]  Hiroshi Yoshida,et al.  A dynamic rate switching method for live video streaming using a smart device , 2015, 2015 21st Asia-Pacific Conference on Communications (APCC).

[4]  Thorsten Herfet,et al.  Server-driven rate control for adaptive video streaming using virtual client buffers , 2014, 2014 IEEE Fourth International Conference on Consumer Electronics Berlin (ICCE-Berlin).

[5]  Abdelhamid Mellouk,et al.  Survey on machine learning-based QoE-QoS correlation models , 2014, 2014 International Conference on Computing, Management and Telecommunications (ComManTel).

[6]  Huifang Chen,et al.  An artificial-neural-network-based QoE estimation model for Video streaming over wireless networks , 2013, 2013 IEEE/CIC International Conference on Communications in China (ICCC).

[7]  Jie Li,et al.  Impact of end-user playout buffer dynamics on HTTP progressive video QoE in wireless networks , 2014, 2014 IEEE 25th Annual International Symposium on Personal, Indoor, and Mobile Radio Communication (PIMRC).

[8]  Chia-Wen Lin,et al.  Buffer-based smooth rate adaptation for dynamic HTTP streaming , 2013, 2013 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference.

[9]  Cyril Concolato,et al.  Overhead and performance of low latency live streaming using MPEG-DASH , 2014, IISA 2014, The 5th International Conference on Information, Intelligence, Systems and Applications.

[10]  Masayuki Murata,et al.  Joint Bearer Aggregation and Control-Data Plane Separation in LTE EPC for Increasing M2M Communication Capacity , 2014, GLOBECOM 2014.

[11]  Zhongwei Zhang,et al.  QoE-aware cross-layer architecture for video traffic over Internet , 2014, 2014 IEEE REGION 10 SYMPOSIUM.

[12]  Xuemin Shen,et al.  Impact of Network Dynamics on User's Video Quality: Analytical Framework and QoS Provision , 2010, IEEE Transactions on Multimedia.