CIF: Small: Collaborative Research: Wireless Networks: Fundamental Limits via Extremal Entropy Properties

到岸价：小号：合作研究：无线网络：利用极值熵特性描述网络通信的基本性能极限是信息论的一个传统。然而，大多数历史上的成功都依赖于一个特殊的极值熵不等式：香农和斯塔姆的熵-幂不等式，虽然它很强大，但主要适用于具有某种退化结构的网络。此外，无线功能，如多输入多输出（MIMO）通信，信道的不确定性引起的衰落，和保密的限制，由于广播性质的无线电通信带来了新的挑战，不能克服的熵功率不等式的香农和斯塔姆单独。这就要求深入研究网络信息论中的匡威问题与统计学中的极值熵性质之间的相互作用，借助强有力的统计工具解决重要的通信工程问题，本研究的具体目标是：1）通过信息论与统计学的联系，系统地研究建立极值熵性质的方法; 2）建立信道增强作为解决MIMO下行链路通信的匡威问题的一般框架;以及3）识别用于解决认知无线网络中协作通信的匡威问题的一般框架。近年来，在设计新的编码方案以实现无线网络的更好性能方面已经做出了大量努力。因此，从工程的角度来看，这些编码方案的限制的基本理解是非常重要的，以指导未来的研究，防止过度工程和支持简单和结构化的编码方案的信心。从这项研究中获得的知识成果也将通过网络信息理论和无线通信在得克萨斯州A M和夏威夷大学的课程开发传播。

CIF: Small: Collaborative Research: Wireless Networks: Fundamental Limits via Extremal Entropy PropertiesUsing extremal entropy properties to characterize the fundamental performance limits of network communication is a tradition of information theory. Most historical successes, however, relied on one particular extremal entropy inequality: the entropy-power inequality of Shannon and Stam, which, though powerful, applies mainly to networks with certain degradedness structure. Moreover, wireless features such as multiple-input multiple-output (MIMO) communications, channel uncertainty incurred by fading, and secrecy constraints due to the broadcast nature of radio communication bring new challenges that cannot be overcome by the entropy-power inequality of Shannon and Stam alone. This situation calls for in-depth investigations of the interaction between converse problems in network information theory and extremal entropy properties in statistics, resorting to powerful statistical tools to solve important communication engineering problems.The specific goals of this research are: 1) to examine systematic ways of establishing extremal entropy properties through links between information theory and statistics; 2) to establish channel-enhancement as a general framework for solving the converse problems for MIMO downlink communication; and 3) to identify general frameworks for solving the converse problems for collaborative communication in cognitive wireless networks. Recent years have seen substantial efforts in designing new coding schemes to achieve better performance for wireless networks. Fundamental understanding of the limits of these coding schemes is thus extremely important from the engineering viewpoint to direct future research and to prevent over-engineering and bolster confidence for simple and structured coding schemes. Intellectual results obtained from this research will also be disseminated via course developments on network information theory and wireless communications at Texas A&M and the University of Hawaii.