CIF: Small: Novel (Channel Modeling, Feedback, and Cognitive) Approaches in Wireless Communications

CIF：小型：无线通信中的新颖（信道建模、反馈和认知）方法

• 批准号: 1115645
• 负责人: Bhaskar Rao
• 金额: $ 46.79万
• 依托单位: University of California-San Diego
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-08-01 至 2015-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1115645&HistoricalAwards=false
• 关键词: CIF; Small; Novel; Channel; Modeling

Wireless communication networks continue to get more complex. Communication over unused TV bands (cognitive radios), self-organizing ad-hoc networks for military and emergency applications, or the heterogeneous networks envisioned in the next generation cellular (LTE advanced) systems all are clear evidence of this trend. As consumer demands, dependence on wireless services, and the complexity of networks continue to grow, there is a need to manage the resources efficiently without overburdening the network owner and end user. To address these challenges, this research involves significant and novel enhancements to the building blocks of modern communication systems. The modeling, feedback, and cognitive techniques being studied in this project are essential for the development of robust and efficient wireless systems. The research project involves the following three parts: 1) Development of novel channel modeling methods that decompose the channel into a specular component and a diffuse component. A key consideration in this work is developing a rigorous framework for channel prediction and utilizing the insight to develop robust feedback based Multiple Input Multiple Output (MIMO) systems that degrade gracefully. 2) The development and analysis of feedback based multi-user MIMO-OFDM systems. This includes novel channel estimation and representations schemes, novel schemes for encoding sparsity, and performance analysis of reduced feedback MIMO-OFDM systems. 3) The development of advanced cognition at the physical layer. This includes waveform design in cognitive radios based on timing consideration and more comprehensive models for channels to provide awareness based on location, learning and memory.

无线通信网络继续变得更加复杂。通过未使用的电视频段（认知无线电）进行的通信、用于军事和紧急应用的自组织自组织网络或下一代蜂窝（LTE 高级）系统中设想的异构网络都是这一趋势的明显证据。随着消费者的需求、对无线服务的依赖以及网络的复杂性不断增长，需要有效地管理资源而不给网络所有者和最终用户带来过重的负担。为了应对这些挑战，这项研究对现代通信系统的构建模块进行了重大而新颖的增强。该项目中正在研究的建模、反馈和认知技术对于开发稳健且高效的无线系统至关重要。 该研究项目包括以下三个部分： 1）开发新颖的通道建模方法，将通道分解为镜面反射分量和漫反射分量。这项工作的一个关键考虑因素是开发严格的信道预测框架，并利用这种洞察力开发基于稳健反馈的多输入多输出 (MIMO) 系统，该系统可以优雅地降级。 2) 基于反馈的多用户MIMO-OFDM系统的开发和分析。这包括新颖的信道估计和表示方案、编码稀疏性的新颖方案以及减少反馈的 MIMO-OFDM 系统的性能分析。 3）物理层高级认知的发展。这包括基于时序考虑的认知无线电波形设计，以及更全面的信道模型，以提供基于位置、学习和记忆的感知。