Collaborative Research: Subspace Expansions for Optimization of Transceivers in Multiple Access Communication

协作研究：多址通信中收发器优化的子空间扩展

• 批准号: 0515061
• 负责人: Hongya Ge
• 金额: --
• 依托单位: New Jersey Institute of Technology
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-09-01 至 2007-11-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0515061&HistoricalAwards=false
• 关键词: Collaborative; Research; Subspace; Expansions; Optimization

This research is directed to subspace signal processing for space-time processing of wireless transmissions to and from the internet, between fixed computers, or between computers and peripherals. It applies particularly to wireless channels that spread signals in space and time, thereby forcing the transceiver to adaptively trade off array and filter gain for diversity in order to achieve satisfactory performance.The research (i) continues our exploitation of the connection between optimization theory and filtering; (ii) advances the state-of-the-art in reduced rank filter design for space-time adaptive processing (STAP); and (iii) applies the results to space-time wireless communication, imaging, and beamforming. The aim is to couple transmitter design to receiver design in wireless communication systems by showing how code design and power control directly influence the cost, complexity and convergence of receivers within a wireless network. The project consists of these elements: (i) downlink cooperative transceiver optimization, using code design, power control, and the vector conjugate gradient Wiener filter to achieve warp convergence; (ii) uplink transceiver optimization, using the matrix conjugate gradient Wiener filter to achieve convergence in one step.

本研究的方向是子空间信号处理，用于互联网、固定计算机之间或计算机与外围设备之间的无线传输的时空处理。它特别适用于在空间和时间上传播信号的无线信道，从而迫使收发器自适应地权衡阵列和滤波器增益以获得分集，以获得令人满意的性能。本研究(1)继续探索优化理论与滤波之间的联系；（ii）提出了用于时空自适应处理（STAP）的最先进的降阶滤波器设计；（iii）将结果应用于时空无线通信、成像和波束形成。目的是通过展示代码设计和功率控制如何直接影响无线网络中接收器的成本、复杂性和收敛性，将无线通信系统中的发射器设计与接收器设计耦合起来。该项目由以下几个部分组成：(i)下行协同收发优化，利用代码设计、功率控制和矢量共轭梯度维纳滤波器实现翘曲收敛；（ii）上行收发器优化，采用矩阵共轭梯度维纳滤波器实现一步收敛。