Constructive approaches for network source coding

网络源编码的建设性方法

• 批准号: RGPIN-2018-05719
• 负责人: Dumitrescu, Sorina
• 金额: $ 2.84万
• 依托单位: McMaster University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2019
• 资助国家: 加拿大
• 起止时间: 2019-01-01 至 2020-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=687305
• 关键词: Constructive; approaches; network; source; coding

Network source coding refers to data compression in network scenarios, i.e., where there is more than one transmitter, or more than one receiver, or both. Traditional data compression techniques, devised for the situation where a single source is to be reconstructed at a single destination, are suboptimal for the complex network scenarios that have emerged lately, and thus, may lead to a waste of bandwidth resources. Therefore, the investigation of techniques for network source coding are of great interest. Their study from an information theoretical point of view establishes fundamental limits of performance, but such results are based on random coding arguments, which are nonconstructive. For practical use, constructive approaches are needed. ******This research will develop novel and efficient constructive network source coding schemes for several network scenarios, as follows: 1) robust distributed compression of correlated sources; 2) networks with one transmitter and more receivers with side information; 3) Slepian-Wolf coding over broadcast channels. The general approach will be to devise coding schemes based on vector quantizers (VQ) with structured codebooks. Specifically, we will employ VQs with lattice codebooks and shape-gain VQs with uniform shape codebooks. We will draw inspiration from the random coding schemes used to derive the achievable rate-distortion regions, where available, or from constructions used in related problems. We will analyze the asymptotical performance under the high rate assumption and, based on this analysis, design asymptotically optimal schemes. Additionally, in the case of shape-gain VQs, we will design algorithms to optimize the codes for finite rates. ******This research aims at designing network source coding schemes which use the available bandwidth more efficiently and provide a guarantee on the quality of service. By accomplishing this goal our research will lay the foundation of novel technologies, which have the potential of making their way in the development of future standards related to multimedia networking. The implementation of such technologies will present an economic opportunity to Canadian information technology companies, and will ultimately be of benefit to consumers of internet services. On the theoretical side, the proposed research will advance the knowledge and understanding in the area of network source code design and analysis. The techniques and insights developed will be also applicable to other more complex network source coding problems which may arise in the future.******An important component of this research will be the training of highly qualified personnel. Several graduate students will be engaged in this research and will be trained in multimedia coding and communications, information theory and optimization. This training will prepare them for an engineering or academic career in the information technology sector.

网络源编码是指网络场景中的数据压缩，即，其中存在多于一个的发射机、或多于一个的接收机、或两者。传统的数据压缩技术，设计的情况下，一个单一的源是在一个单一的目的地重建，是次优的复杂网络的情况下，最近出现的，因此，可能会导致带宽资源的浪费。因此，网络信源编码技术的研究具有重要意义。他们的研究从信息理论的角度建立了基本的性能限制，但这样的结果是基于随机编码参数，这是非建设性的。为了实际使用，需要采取建设性的办法。** 本研究将为以下几种网络场景开发新颖且有效的建设性网络信源编码方案：1）相关信源的鲁棒分布式压缩; 2）具有一个发射机和多个接收机的网络，具有边信息; 3）广播信道上的Slepian-Wolf编码。一般的方法将是设计编码方案的基础上矢量量化器（VQ）与结构化码本。具体地，我们将采用具有格形码本的VQ和具有均匀形状码本的形状增益VQ。我们将从用于获得可实现的率失真区域的随机编码方案中获得灵感，或者从相关问题中使用的构造中获得灵感。我们将分析在高速率假设下的渐近性能，并基于此分析，设计渐近最优方案。此外，在形状增益VQ的情况下，我们将设计算法来优化有限速率的代码。** 本研究旨在设计网络信源编码方案，更有效地利用可用带宽，并提供服务质量的保证。通过实现这一目标，我们的研究将奠定新技术的基础，这有可能使他们的方式在未来的标准发展相关的多媒体网络。这些技术的实施将为加拿大信息技术公司提供经济机会，并最终使互联网服务的消费者受益。在理论方面，本文的研究将促进网络源代码设计和分析领域的知识和理解。所开发的技术和见解也将适用于未来可能出现的其他更复杂的网络源编码问题。这项研究的一个重要组成部分将是培训高素质的人员。一些研究生将从事这项研究，并将在多媒体编码和通信，信息理论和优化培训。这项培训将为他们在信息技术部门的工程或学术生涯做好准备。