Network Channel Coding for Packet Video
Network Channel Coding for Packet Video
批准号:
0515253
负责人:
Hayder Radha
金额:
$24.39万
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2005
资助国家:
美国
项目状态:
已结题
起止时间:
2005-09-01 至 2009-08-31
中文摘要
已经使用了广泛的端到端信道编码技术来支持因特网和其他分组网络上的分组视频应用。然而,传统的端到端前向纠错(FEC)技术不能很好地扩展,特别是对于大型网络,因为在底层分布树的深层节点处存在大量的分组丢失。同时,新兴的网络模式,如覆盖、对等和自组织无线网络,为向大量接收者提供实时视频的新方法打开了大门,同时保持高水平的可靠性和吞吐量。在该研究项目中,研究和开发了一种新的框架,网络信道编码(NCC),它利用新兴的网络模式,如对等网络和覆盖网络。这项研究针对通用网络应用优化了NCC,重点是优化分组视频应用、它们的整体质量以及它们对大量接收器的吞吐量。特别是,正在研究、分析和设计用于在任意网络拓扑(即,任意图)内嵌入和分布信道编码函数的最佳解决方案。在类似率失真(RD)的框架下使用成本最小化来开发NCC优化,该框架在最大化吞吐量的同时最小化整个网络的NCC开销。该框架揭示了用于最大吞吐量和最小失真分组视频应用的关键理论限制和相应的最优NCC解决方案。此外,还在开发实用的分布式NCC算法。虽然这些分布式NCC算法本质上是通用的,但它们非常适合于对等和自组织无线系统上的分组视频。此外,在优化NCC框架的背景下,正在探索和开发新兴领域的新扩展,例如LDPC码、跨层通信和网络(源)编码。
英文摘要
A wide range of end-to-end channel coding techniques have been used in support of packet video applications over the Internet and other packet networks. Traditional end-to-end Forward-Error-Correction (FEC) techniques do not scale well though, and especially for large networks due to the large number of packet losses at deep nodes of the underlying distribution tree. Meanwhile, emerging network paradigms, such as overlay, peer-to-peer, and ad-hoc wireless networks, open the door for new approaches of delivering real-time video to a large number of receivers while maintaining high level of reliability and throughput.Under this research project, a new framework, Network Channel Coding (NCC), that exploits emerging networking paradigms, such as peer-to-peer and overlay networks, are investigated and developed. This research optimizes NCC for generic network applications with emphasis on optimizing packet-video applications, their overall quality, and their throughput to a large number of receivers. In particular, optimum solutions for embedding and distributing channel coding functions within arbitrary network topologies (i.e., arbitrary graphs) are being investigated, analyzed, and designed. NCC optimization is being developed using cost-minimization under a rate-distortion (RD) like framework that maximizes throughput while minimizing the NCC overhead throughout the network. This framework reveals key theoretical limits and corresponding optimum NCC solutions that can be achieved for maximum-throughput and minimum-distortion packet video applications. Furthermore, practical and distributed NCC algorithms are being developed. Although general in nature, these distributed NCC algorithms are well suited for packet video over peer-to-peer and ad-hoc wireless systems. Furthermore, novel extensions in emerging areas, such as LDPC codes, cross-layer communications, and network (source) coding, are being explored and developed in the context of the optimization NCC framework.
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