QoE Aware Resource Allocation for Multi-view Video Flows in LTE

Recently, the popularity of multi-view video flow transmission over cellular networks has received a significant surge. However, due to considerably higher bandwidth demands compared to conventional 2D videos, efficient resource allocation techniques specially oriented towards multi-view video must be designed to allow their efficient transmission. From the perspective of maintaining a minimum acceptable Quality of Experience (QoE) for each active user even during overload situations, adaptive 3D multi-view video streaming is being widely viewed as a promising enabling technology. Leveraging this technology, we first pose the problem of scheduling a set of multi-view videos as an optimization problem which attempts to maximize aggregate QoE. In addition, a heuristic solution to the optimization problem has been designed. Simulation results show that the proposed strategy is able to effectively deliver satisfactory the average playback-quality while simultaneously minimizing bit-rate switching in the video output.

[1]  Martin Reisslein,et al.  Traffic and Quality Characterization of Single-Layer Video Streams Encoded with the H.264/MPEG-4 Advanced Video Coding Standard and Scalable Video Coding Extension , 2008, IEEE Transactions on Broadcasting.

[2]  Mung Chiang,et al.  A scheduling framework for adaptive video delivery over cellular networks , 2013, MobiCom.

[3]  Giuseppe Piro,et al.  Simulating LTE Cellular Systems: An Open-Source Framework , 2011, IEEE Transactions on Vehicular Technology.

[4]  A. Murat Tekalp,et al.  Evaluation of adaptation methods for multi-view video , 2012, 2012 19th IEEE International Conference on Image Processing.

[5]  Giuseppe Piro,et al.  3D Video transmissions over LTE: A performance evaluation , 2013, Eurocon 2013.

[6]  Arnab Sarkar,et al.  A resource allocation framework for adaptive video streaming over LTE , 2017, J. Netw. Comput. Appl..

[7]  Christian Bettstetter,et al.  Mobility modeling in wireless networks: categorization, smooth movement, and border effects , 2001, MOCO.

[8]  Satish Kumar,et al.  A QoE Aware SVC Based Client-side Video Adaptation Algorithm for Cellular Networks , 2018, ICDCN.

[9]  Mahbub Hassan,et al.  Optimizing HTTP-Based Adaptive Streaming in Vehicular Environment Using Markov Decision Process , 2015, IEEE Transactions on Multimedia.

[10]  Wanjiun Liao,et al.  Efficient multi-view 3D video multicast with depth image-based rendering in LTE networks , 2013, 2013 IEEE Globecom Workshops (GC Wkshps).

[11]  Satish Kumar,et al.  A three level LTE downlink scheduling framework for RT VBR traffic , 2015, Comput. Networks.

[12]  Ahmet M. Kondoz,et al.  Dynamic adaptive 3D multi-view video streaming over the internet , 2013, ImmersiveMe '13.

[13]  Ronit Nossenson.  Long-term evolution network architecture , 2009, 2009 IEEE International Conference on Microwaves, Communications, Antennas and Electronics Systems.