Collaborative Research: Systematic Optimization in Wireless Multicasting

合作研究：无线组播系统优化

• 批准号: 0728826
• 负责人: Jie Luo
• 金额: $ 16.6万
• 依托单位: Colorado State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-09-15 至 2011-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0728826&HistoricalAwards=false
• 关键词: Collaborative; Research; Systematic; Optimization; Wireless

Research AbstractMulticasting, where common information is transmitted from a source to multiple destinations,is the core component of many network applications such as multimedia distribution, information update, group conferencing, etc. Creative encoding of network trac at the intermediate terminals can signicantly improve the throughput of a multicast over conventional replicate-and-forward approaches. Due to the open nature of the wireless medium, communication throughput of a wireless link depends on its transmission power and on the interference generated by nearby network terminals. The goal of this research is to develop a systematic framework for maximizing a generalmulticast utility function via the joint optimization of transmission power, rate, and schedule,within the framework of network coding.The investigators model a wireless ad hoc network by means of a topology graph, which contains point-to-point links and point-to-multipoint hyperarc links with coupled link throughput capacities. Under the assumption of optimal network coding, the research first develops an iterative gradient-steering" optimization framework. A network utility maximization problem is convertedto a transmission scheduling problem that maximizes an approximated utility in its gradient direction, coupled with a steering vector update that continuously updates the approximated utility and its instantaneous gradient direction. The research then extends the framework to utility max-imization for a network with multiple multicast sessions. Finally, the research develops distributed algorithms to optimize a global utility of a large scale network using local controllers. In addition to the planned research, the investigators will also try to extend the algorithm to ad hoc networks with time varying channels where utility maximization requires efficient exploitation of the channel diversity gain.

研究摘要多播是将公共信息从源传输到多个目的地，是多媒体分发、信息更新、群组会议等许多网络应用的核心组件。与传统的复制转发方法相比，在中间终端对网络跟踪进行创造性编码可以显着提高多播的吞吐量。由于无线介质的开放性，无线链路的通信吞吐量取决于其传输功率以及附近网络终端产生的干扰。本研究的目标是在网络编码框架内开发一个系统框架，通过传输功率、速率和调度的联合优化来最大化通用组播效用函数。研究人员通过拓扑图对无线自组织网络进行建模，该网络包含点对点链路和具有耦合链路吞吐量的点对多点超弧链路。在最优网络编码的假设下，该研究首先开发了“迭代梯度引导”优化框架。将网络效用最大化问题转化为在梯度方向上最大化近似效用的传输调度问题，再加上不断更新近似效用及其瞬时梯度方向的引导向量更新。然后，该研究将该框架扩展到具有多个网络的效用最大化。 多播会话。最后，该研究开发了分布式算法，以使用本地控制器优化大规模网络的全局效用。除了计划的研究之外，研究人员还将尝试将该算法扩展到具有时变信道的自组织网络，其中效用最大化需要有效利用信道分集增益。