Optimal Multi-View Video Transmission in Multiuser Wireless Networks by Exploiting Natural and View Synthesis-Enabled Multicast Opportunities

Multi-view videos (MVVs) provide immersive viewing experience, at the cost of traffic load increase for wireless networks. In this paper, we would like to optimize MVV transmission in a multiuser wireless network by exploiting both natural multicast opportunities and view synthesis-enabled multicast opportunities. Specifically, we first establish a mathematical model to specify view synthesis at the server and each user, and characterize its impact on multicast opportunities. This model is highly nontrivial and fundamentally enables the optimization of view synthesis-based multicast opportunities. For given video quality requirements of all users, we consider the optimization of view selection, transmission time and power allocation to minimize the average weighted sum energy consumption for view transmission and synthesis. In addition, under the energy consumption constraints at the server and each user respectively, we consider the optimization of view selection, transmission time and power allocation and video quality selection to maximize the total utility. These two optimization problems are challenging mixed discrete-continuous optimization problems. For the first problem, we propose an algorithm to obtain an optimal solution with reduced computational complexity by exploiting optimality properties. For each problem, to reduce computational complexity, we also propose a low-complexity algorithm to obtain a suboptimal solution, using Difference of Convex (DC) programming. Finally, numerical results show the advantage of the proposed solutions over existing ones, and demonstrate the importance of the optimization of view synthesis-enabled multicast opportunities in MVV transmission.

[1]  Pascal Frossard,et al.  Interactive free viewpoint video streaming using prioritized network coding , 2013, 2013 IEEE 15th International Workshop on Multimedia Signal Processing (MMSP).

[2]  Thomas Wiegand,et al.  3D Video and Free Viewpoint Video - Technologies, Applications and MPEG Standards , 2006, 2006 IEEE International Conference on Multimedia and Expo.

[3]  Hoang Duong Tuan,et al.  Nonsmooth Optimization for Efficient Beamforming in Cognitive Radio Multicast Transmission , 2012, IEEE Transactions on Signal Processing.

[4]  Jaime Llorca,et al.  Energy efficient delivery of immersive video centric services , 2012, 2012 Proceedings IEEE INFOCOM.

[5]  Geyong Min,et al.  QoS-aware energy-efficient multicast for multi-view video with Fractional Frequency Reuse , 2015, 2015 10th International Conference on Communications and Networking in China (ChinaCom).

[6]  Quanxin Zhao,et al.  QoS-aware energy-efficient multicast for multi-view video in indoor small cell networks , 2014, 2014 IEEE Global Communications Conference.

[7]  Pascal Frossard,et al.  Optimizing Multiview Video Plus Depth Prediction Structures for Interactive Multiview Video Streaming , 2015, IEEE Journal of Selected Topics in Signal Processing.

[8]  Christoph Fehn,et al.  Depth-image-based rendering (DIBR), compression, and transmission for a new approach on 3D-TV , 2004, IS&T/SPIE Electronic Imaging.

[9]  Takashi Watanabe,et al.  UMSM: A Traffic Reduction Method on Multi-View Video Streaming for Multiple Users , 2014, IEEE Transactions on Multimedia.

[10]  Aljoscha Smolic,et al.  Interactive 3-D Video Representation and Coding Technologies , 2005, Proceedings of the IEEE.

[11]  Yao Zhao,et al.  A packetization strategy for interactive multiview video streaming over lossy networks , 2018, Signal Process..

[12]  Pascal Frossard,et al.  In-Network View Synthesis for Interactive Multiview Video Systems , 2015, IEEE Transactions on Multimedia.

[13]  Pascal Frossard,et al.  Adaptive Streaming in Interactive Multiview Video Systems , 2018, IEEE Transactions on Circuits and Systems for Video Technology.

[14]  Stephen P. Boyd,et al.  Variations and extension of the convex–concave procedure , 2016 .

[15]  Pascal Frossard,et al.  Optimal Representations for Adaptive Streaming in Interactive Multiview Video Systems , 2017, IEEE Transactions on Multimedia.

[16]  Pascal Frossard,et al.  Optimized MVC Prediction Structures for Interactive Multiview Video Streaming , 2013, IEEE Signal Processing Letters.

[17]  Stephen P. Boyd,et al.  Notes on Decomposition Methods , 2008 .

[18]  Jacob Chakareski,et al.  User-Action-Driven View and Rate Scalable Multiview Video Coding , 2013, IEEE Transactions on Image Processing.

[19]  Aljoscha Smolic,et al.  Efficient Prediction Structures for Multiview Video Coding , 2007, IEEE Transactions on Circuits and Systems for Video Technology.

[20]  Ying Cui,et al.  Optimal Multicast of Tiled 360 VR Video , 2018, IEEE Wireless Communications Letters.

[21]  Wei Xu,et al.  Energy-Efficient Multi-View Video Transmission with View Synthesis-Enabled Multicast , 2018, 2018 IEEE Global Communications Conference (GLOBECOM).

[22]  Pascal Frossard,et al.  Optimized receiver control in interactive multiview video streaming systems , 2017, 2017 IEEE International Conference on Communications (ICC).

[23]  Ning Yang,et al.  Augmented reality multi-view video scheduling under vehicle-pedestrian situations , 2015, 2015 International Conference on Connected Vehicles and Expo (ICCVE).

[24]  Aljoscha Smolic,et al.  Multi-View Video Plus Depth Representation and Coding , 2007, 2007 IEEE International Conference on Image Processing.

[25]  Gary J. Sullivan,et al.  Overview of the Stereo and Multiview Video Coding Extensions of the H.264/MPEG-4 AVC Standard , 2011, Proceedings of the IEEE.

[26]  Yusheng Ji,et al.  Optimizing Distributed Source Coding for Interactive Multiview Video Streaming Over Lossy Networks , 2013, IEEE Transactions on Circuits and Systems for Video Technology.

[27]  Dimitri P. Bertsekas,et al.  Nonlinear Programming , 1997 .

[28]  Ajay Luthra,et al.  Overview of the H.264/AVC video coding standard , 2003, IEEE Trans. Circuits Syst. Video Technol..