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Adaptive residual-based distributed compressed sensing for soft video multicasting over wireless networks

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Abstract

Recently, multicasting of video signals has become a useful technology in wireless networks, in which the main challenge is to scalably serve multiple receivers that have different channel characteristics. In this paper, we propose an adaptive residual-based distributed compressed-sensing scheme for soft video multicast (ARDCS-cast). At the encoder, we first adaptively determine if a block in a non-reference frame should be measured directly or predictively during compressed-sensing. The resulting adaptive measurements from non-reference frames are then packeted together with the measurements of the reference frames. We further derive the optimal power allocation scheme for the measurements from each frame within each packet. The packets are then transmitted over the wireless channel. At the decoder, the receivers with different channel characteristics obtain different numbers of packets and reconstruct videos with different quality. Experimental results show that the proposed ARDCS-cast is more effective than the state-of-the-art SoftCast-2D, SoftCast-3D and DCS-cast schemes in both unicast and multicast scenarios.

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Acknowledgments

This work has been supported in part by National Natural Science Foundation of China (No. 61272262 and No. 61210006), The Program of “One hundred Talented People” of Shanxi Province, Research Project Supported by Shanxi Scholarship Council of China (2014-056), Program for New Century Excellent Talent in Universities (NCET-12-1037), International Cooperative Program of Shanxi Province (No. 2015081015), Scientific and Technological project of Shanxi Province (2015031003-2), and National Science Foundation for Young Scientists of Shanxi Province, China (2014021021-2)

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Authors and Affiliations

  1. Institute of Digital Multimedia and Communication, Taiyuan University of Science and Technology, Taiyuan, 030024, China

    Shanshan Liu, Anhong Wang, Haidong Wang, Suyue Li & Meiling Li

  2. School of Engineering Science, Simon Fraser University, Burnaby, BC, Canada

    Jie Liang

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  1. Shanshan Liu
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  2. Anhong Wang
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  3. Haidong Wang
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  4. Suyue Li
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  5. Meiling Li
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  6. Jie Liang
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Correspondence to Anhong Wang.

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Liu, S., Wang, A., Wang, H. et al. Adaptive residual-based distributed compressed sensing for soft video multicasting over wireless networks. Multimed Tools Appl 76, 15587–15606 (2017). https://doi.org/10.1007/s11042-016-3859-3

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