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

由于用户希望在笔记本电脑和手持设备上观看电视直播和体育赛事，无线视频组播越来越受欢迎。然而，问题是无线用户具有非常不同的信道特性。将视频单独传输给每个用户是不可扩展的，但是传输单个视频流以服务于所有用户的不同频道是一个具有挑战性的问题。该项目引入了数字雨，这是一种将视频流传输到不同无线接收器的新范例。Digital Rain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，其中源只广播属于视频流的编码分组。接收器利用所有接收到的视频分组，即使是那些有误码的分组。接收器收集更多的包，或在每个包中经历更少的误码，可以看到更高的视频质量，而不需要接收器反馈、重新传输或改变编解码器的速率。这项研究在压缩感知理论和实际的无线网络设计之间建立了一座桥梁。此外，它显著提高了无线视频组播的可扩展性，并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产生了直接和广泛的影响。这项研究是与教育计划相结合和协同的，除了标准的研究生和本科生研究和课程开发外，该计划还直接支持麻省理工学院为女性和代表性不足的少数群体提供更有教养的环境的努力。最后，与之前资助的工作一样，该项目将产生开放源代码、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.