Collaborative Research: Cognitive Ad Hoc Networks: Capacity Optimization Through Local Adaptation

协作研究：认知自组织网络：通过本地适应进行容量优化

• 批准号: 0634979
• 负责人: Jeffrey Andrews
• 金额: $ 11.5万
• 依托单位: University of Texas at Austin
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-10-01 至 2009-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0634979&HistoricalAwards=false
• 关键词: Collaborative; Research; Cognitive; Ad; Hoc

Title: Collaborative Research: Cognitive Ad Hoc Networks: Capacity Optimization Through Local Adaptation0635003, Weber0634979, Andrews0634763, JindalDue to the unpredictability of the environment in which unplanned (ad hoc) wireless networks will operate, an appealing approach is to allow the network to dynamically adapt to the perceived conditions. We define such ad hoc networks as cognitive. A framework is developed for understanding the benefits of local adaptation, by breaking adaptive techniques into the four major degrees of freedom available to the designer: time, frequency, code, and space. The aim is to address the following two questions. First, what are the fundamental limits on information flow through unplanned networks; in particular, how valuable is localized information and coordination in seeking to achieve this limit? Second, what are the relative values of adaptation in time, space, frequency, and code in terms of information flow; in particular, how does the network designer identify which degree of freedom is most valuable in a variety of networking scenarios?In this research, information theory and stochastic geometry are connected through a novel metric for ad hoc network capacity, termed the transmission capacity. This metric captures the maximum spatial intensity of transmissions subject to a specified outage probability. While related to other popular capacity metrics, notably the transport capacity, the transmission capacity is unique in its allowance of explicit and accurate characterization of capacity for any conceivable communication scheme or transmission environment. The transmission capacity is an indispensable unifying metric for this analysis since i) it allows closed-form results, ii) does not require any global coordination or optimization, iii) accurately models the interference environment of an ad hoc network. These innovations will allow a basis for more efficient wireless network design.

标题：协作研究：认知自组网络：通过局部适应进行容量优化0635003，Weber0634979，Andrews0634763，Jindal由于计划外（自组）无线网络运行环境的不可预测性，一种有吸引力的方法是允许网络动态适应到感知到的条件。我们将这种自组织网络定义为认知网络。通过将自适应技术分解为设计者可用的四个主要自由度：时间、频率、代码和空间，开发了一个框架来理解本地自适应的好处。 目的是解决以下两个问题。 首先，通过计划外网络进行信息流动的根本限制是什么？特别是，本地化信息和协调对于寻求实现这一限制有多大价值？ 第二，时间、空间、频率、编码的适应对于信息流的相对价值是多少？特别是，网络设计者如何确定在各种网络场景中哪种自由度最有价值？在这项研究中，信息论和随机几何通过一种新的自组织网络容量度量（称为传输容量）连接起来。 该指标捕获指定中断概率下传输的最大空间强度。 虽然与其他流行的容量度量（尤其是传输容量）相关，但传输容量的独特之处在于它允许对任何可想象的通信方案或传输环境的容量进行明确且准确的表征。传输容量是此分析不可或缺的统一指标，因为 i) 它允许封闭形式的结果，ii) 不需要任何全局协调或优化，iii) 准确地模拟自组织网络的干扰环境。 这些创新将为更高效的无线网络设计奠定基础。