NeTS-ANET: One Video Multicast to Serve Diverse Wireless Receivers

无线视频多播越来越受欢迎，这是由于用户希望在膝上型计算机和手持设备上观看直播电视和体育赛事。然而，问题是无线用户具有非常不同的信道特性。将视频分别传输给每个用户是不可扩展的，然而，传输一个单一的视频流，服务于所有用户，尽管他们的不同渠道是一个具有挑战性的问题。这个项目介绍了数字雨，一个新的范例流视频异构无线接收器。 数字雨建立在压缩感知理论的基础上，开发了一种新的视频组播方法，其中源简单地广播属于视频流的编码数据包。 接收器利用所有接收到的视频数据包，即使是那些有位错误的。 接收端收集更多的数据包，或者每个数据包中的比特错误更少，可以看到更高的视频质量，而不需要接收端反馈、重传或改变编解码器的速率。 此外，它显著地提高了无线视频多播的可扩展性，并且因此对新兴的无线视频应用（例如，IPTV，或互联网协议电视），以及相应的无线行业。 该研究与一项教育计划相结合，并具有协同作用，除了标准的研究生和本科生研究和课程开发外，还直接支持麻省理工学院为妇女和代表性不足的少数民族提供更有利环境的努力。 最后，与以前的资助工作一样，该项目将产生开源、可下载的代码。

Wireless video multicast is increasingly popular, driven by users' desires to watch live TV and sporting events on laptops and handheld devices. The problem however is that wireless users have very different channel characteristics. Transmitting the video separately to each user is unscalable, yet transmitting a single video stream that serves all users despite their diverse channels is a challenging problem.This project introduces Digital Rain, a new paradigm for streaming video to heterogeneous wireless receivers. Digital Rain builds on the theory of compressed sensing to develop a novel approach to video multicast where the source simply broadcasts coded packets belonging to a video stream. Receivers exploit all received video packets, even those with bit errors. Receivers that collect more packets, or experience fewer bit errors in each packet, see higher video quality without any need to receiver feedback, retransmissions, or changing the rate of the codec.This research creates a bridge between the theory of compressed sensing and practical wireless network design. Further, it significantly improves the scalability of wireless video multicast, and hence has a direct and broad impact on emerging wireless video applications (e.g., IPTV, or Television over Internet Protocol), as well as the corresponding wireless industry. The research is integrated and synergistic with an educational plan that, in addition to standard graduate and undergraduate research and course development, directly supports MIT's effort to provide a more nurturing environment for women and underrepresented minorities. Finally, as in previous funded work, the project will result in open source, downloadable code.