MuVi: Multiview video aware transmission over MIMO wireless systems

Publication Type

Journal Article

Publication Date

12-2017

Abstract

Multiview video is essential for various mobile three-dimensional (3D) and immersive applications that can capture scenes from multiple angles for better user experience. However, robust transmission of multiview video is very challenging in wireless networks due to high bandwidth requirement and time-varying channel quality. Though the up-to-date 802.11 system enables spatial multiplexing MIMO to enhance transmission capacity, it is still agnostic to 3D source coding structure in the transmission. In this paper, we study the optimal resource allocation problem in MIMO systems that deliver 3D content with multiview video coding. The basic idea is to exploit the channel diversity of multiple antennas and the source coding characteristics so as to achieve unequal error protection against channel errors. To achieve this goal, we develop a nonlinear mixed integer programming framework to perform antenna selection and power allocation, and propose low-complexity algorithms to assign these resources. We implement a proof-of-concept system, namely MuVi, on the software-defined-radio platform, WARP, to evaluate the proposed algorithms. MuVi is the practical system to tackle 3D multiview streaming in the latest Wi-Fi networks such as IEEE 802.11ac under realistic channel conditions. Extensive experimental results demonstrate that the peak signal-to-noise-ratio of MuVi significantly outperforms that of the conventional power allocation scheme in a variety of indoor environments.

Keywords

Antenna selection, distortion, MIMO, multiview video streaming, power allocation

Discipline

Software Engineering

Research Areas

Software and Cyber-Physical Systems

Publication

IEEE Transactions on Multimedia

Volume

19

Issue

12

First Page

2788

Last Page

2803

ISSN

1520-9210

Identifier

10.1109/TMM.2017.2713414

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Additional URL

https://doi.org/10.1109/TMM.2017.2713414

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