CAREER: A Generalized Compressive Sensing Approach to Data Acquisition and Ad-Hoc Sensor Networking

职业：数据采集和自组织传感器网络的通用压缩传感方法

• 批准号: 1418710
• 负责人: Nazanin Rahnavard
• 金额: $ 33.48万
• 依托单位: The University of Central Florida Board of Trustees
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-01-01 至 2017-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1418710&HistoricalAwards=false
• 关键词: CAREER; Generalized; Compressive; Sensing; Approach

The objective of this project is to advance the field of compressive sensing and broaden its scope into a multitude of new applications, such as ad hoc networking, by significantly enhancing the efficiency through the utilization of problem-specific signals and systems properties. The proposed approach is to design a novel rateless-coding-inspired generalized compressive sensing (GCS) framework and to integrate it into different stages of sensing, information processing, and cross-layer designs in the network design processes.Intellectual Merit: The proposed research bridges the gap between the advanced theoretical research on modern coding and compressive sensing, as to significantly enhance the efficiency of data acquisition and ad hoc networking. GCS offers the flexibility of exploiting problem-specific properties, such as non-uniform sparsity and non-uniform importance of data in the sensing and recovery phases. This is expected to result in a significant reduction in sensing and communication costs. Through cross-layer design of GCS and underlying network protocols, efficient data acquisition and distributed data storage problems in sensor networks will be investigated.Broader Impacts: This proposal is expected to have a significant direct impact on advancing the theory and practice of compressive sensing and an indirect impact on many areas in which compressive sensing has potential application, such as medical imaging, hyper-spectral imaging, and bio-informatics. Furthermore, it expected to have an impact on increasing the participation of under-represented students in the PI's research group, as well as in promoting engineering education among high school students, in integration of research and education through curriculum development/revision, in training graduate students, and in promoting multidisciplinary research and collaboration through initiating ECE Seminar Day Program at OSU.

该项目的目的是通过通过利用特定问题特定的信号和系统属性来显着提高效率，从而将压缩感测的领域提高到众多新应用程序，例如临时网络。所提出的方法是设计一种新型的无重量编码为灵感的广义压缩感（GCS）框架，并将其集成到网络设计过程中的感应，信息处理和跨层设计的不同阶段。启动的研究：拟议的研究弥补了现代编码和适应性效果的高级理论研究之间的差距，并增强了数据的效率，并促进了效果，以增强效率，以增强效率。 GCS提供了利用特定问题的特性的灵活性，例如在感应和恢复阶段中数据的非均匀稀疏性和数据对数据的重要性。预计这将大大降低感应和沟通成本。通过GCS的跨层设计和潜在的网络协议，将研究有效的数据获取和传感器网络中的分布式数据存储问题。Broader的影响：预计该建议将对推进压缩感应的理论和实践产生重大的直接影响，并对压缩感应的许多领域的影响以及对压缩传感具有潜在的应用程序，例如医学上的Impect Image Image Image and bio Image Image and Bio。此外，它预计将对PI研究小组中代表性不足的学生的参与以及在高中生中促进工程教育，通过课程开发/修订，培训研究生研究和教育在培训研究生中以及通过促进ECE ECE ECE Ece Ensiinar DebON启动ECE Ece eNINAR PROPANS来促进研究和教育的参与产生影响。