ITR/SY + SI (C-CR) Collaborative Research: Signal Processing and Channel Modelling in Low-Dimensional Subspaces for Wireless Communication in Multi-Antenna Systems

ITR/SY SI (C-CR) 合作研究：多天线系统无线通信的低维子空间信号处理和信道建模

• 批准号: 0112573
• 负责人: Louis Scharf
• 金额: $ 25万
• 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: 2001
• 资助国家: 美国
• 起止时间: 2001-10-01 至 2004-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0112573&HistoricalAwards=false
• 关键词: ITR; SY; SI; CR; Collaborative

ITR Small Proposal 0112508/ 0112573Friedlander/ScharfTitle: Signal Processing and Channel Modelling in Low-DimensionalSubspaces for Wireless Communication in Multi-Antenna SystemsAbstractThe problem of communicating information between a fixed basestation and many mobile peripherals dominates much of current research in wireless communication. The problem is tecnologically challenging because the channel that connects the basestation to the peripherals is random and time-varying. The most general solution requires space-time coding and signal processing that is "matched" to the channel. The objective of this research program is to extend the theory of space-time array processing (STAP) developed for radar applications, to multi-antenna wireless communication over fading channnels, in order to determine whenand how channel structure can be exploited for space-time signal processing gain and/or diversity. Theoretically, the results of this research advance the understanding of multi-antenna wireless communication between antenna arrays. Practically, they suggest methods for adaptively communicating between fixed basestations and mobiles and between fixed computers and movable storage area networks.Prior results by the principal investigators suggest that only the span of a low-dimensional channel subspace, and not the detailed physics of its coordinate representation, is required for the design of signals that optimize transmit diversity, and tranceivers that optimize the trade off between space-time processing gain and diversity. Moreover, the optimum transceiver statistics are just estimators of output signal-to-interference plus noise ratio (SINR), suggesting that transceiver statistics for decoding data can be used to estimate and track output SINR and network capacity. This means power and bandwidth may be adaptively allocated, using only transceiver statistics. So, in broad outline, this program is addressed to space-time channel modelling, using subspace methods; subspace signal and transceiver design for gain and diversity; and estimation of network capacity, using only transceiver statistics.

ITR小提案0112508/0112573FRIEDLANDER/ SCHARFTITLE：在低二敏化邮件中的信号处理和通道模型，用于在多端式系统中无线通信，以吸收固定底座之间的信息的问题，许多移动外围在无线通信中占据了许多目前的研究。这个问题在杂志上具有挑战性，因为将基础与外围设备连接的通道是随机的且随时间变化的。最通用的解决方案需要与通道“匹配”的时空编码和信号处理。该研究计划的目的是扩展为雷达应用开发的时空阵列处理（Stap）的理论，到褪色通道上的多人无线通信，以确定如何利用通道结构来利用频道结构来实现时空信号处理增益和/或多样性。从理论上讲，这项研究的结果可以使对天线阵列之间的多Antenna无线通信的理解。实际上，他们提出了在固定基础和手机之间以及固定计算机和可移动存储区域网络之间自适应沟通的方法。主要研究人员的优点结果表明，只有一个低维渠道子空间的跨度，而不是其坐标表示的详细物理，而不是优化交易的信号所必需的，以使多样化的贸易量优化，并使得多样化的贸易范围优化，并且可以使超级贸易机之间的差异和差异化。此外，最佳收发器统计仅仅是输出信号与干扰加噪声比（SINR）的估计器，这表明用于解码数据的收发器统计数据可用于估计和跟踪输出SINR和网络容量。这意味着仅使用收发器统计信息可以自适应分配功率和带宽。因此，在广泛的轮廓中，使用子空间方法将该程序定为时空通道建模。子空间信号和收发器设计，以获得增益和多样性；和网络容量的估计，仅使用收发器统计数据。