CSR: Medium: Collaborative Research: Embedded System Design Optimization and Adaptation using Compact System-Level Models

CSR：中：协作研究：使用紧凑系统级模型的嵌入式系统设计优化和适应

• 批准号: 1514425
• 负责人: Shuvra Shikhar Bhattacharyya
• 金额: $ 46.22万
• 依托单位: University of Maryland, College Park
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-07-15 至 2021-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1514425&HistoricalAwards=false
• 关键词: CSR; Medium; Collaborative; Research; Embedded

This project will develop new techniques to help advanced computing systems for signal processing better adapt to the environments in which they operate. This project is important because signal processing is everywhere (cell phones, computer networks, manufacturing systems, agriculture, etc.). Adapting to the environment helps these systems to operate more reliably by, for example, adapting to changing radio interference or the challenging radio environments presented by clusters of tall buildings. Many of these communication systems are also battery-operated or must run on limited energy; adapting to their operating environments helps to reduce their energy consumption and improve battery life. These techniques are particularly useful for cognitive radio, an emerging technology that allows devices for wireless communication (such as cell phones) to more efficiently use radio spectrum.This project will develop new methods for creating software that can be reconfigured at run time. Typical software is created to operate in a particular mode; changing the software's operating conditions requires redesigning the software itself. New mathematical models and algorithms will allow system designers to create software that is designed to adapt itself dynamically to its environment. The project will address both models specifying the behavior of the software and for translating that specification into an efficient implementation.The principal investigators will collaborate with colleagues at the Institut National des Sciences Appliquées (INSA) in Rennes, France, and National Chiao Tung University in Hsinchu, Taiwan. The collaborators in France and Taiwan will provide expertise in cognitive radio algorithms and hardware that complements the principal investigators' expertise in software design. The collaboration will also provide valuable international experience for the student research assistants involved in the project. Cognitive radio will be used as a driving example in coursework for undergraduate and graduate students to integrate research results from this project into education. The PIs will actively recruit underrepresented minority students for this project.

该项目将开发新技术，帮助先进的信号处理计算系统更好地适应其运行环境。这个项目很重要，因为信号处理无处不在（手机、计算机网络、制造系统、农业等）。适应环境有助于这些系统更可靠地运行，例如，适应不断变化的无线电干扰或高层建筑群带来的具有挑战性的无线电环境。许多此类通信系统也是由电池供电或必须以有限的能量运行；适应操作环境有助于降低能耗并延长电池寿命。这些技术对于认知无线电特别有用，认知无线电是一种新兴技术，允许无线通信设备（例如手机）更有效地使用无线电频谱。该项目将开发新方法来创建可以在运行时重新配置的软件。典型的软件是为了在特定模式下运行而创建的；改变软件的运行条件需要重新设计软件本身。新的数学模型和算法将允许系统设计人员创建能够动态适应环境的软件。该项目将解决指定软件行为的两个模型，并将该规范转化为有效的实现。主要研究人员将与法国雷恩国家应用科学研究所 (INSA) 和台湾新竹国立交通大学的同事合作。法国和台湾的合作者将提供认知无线电算法和硬件方面的专业知识，以补充主要研究人员在软件设计方面的专业知识。此次合作还将为参与该项目的学生研究助理提供宝贵的国际经验。认知无线电将作为本科生和研究生课程作业的驱动示例，将该项目的研究成果融入到教育中。 PI 将积极招募代表性不足的少数族裔学生参与该项目。