High Efficiency Distributed Beamforming RF Energy Transfer using a Closed-loop Energy Receiver
使用闭环能量接收器进行高效分布式波束成形射频能量传输
基本信息
- 批准号:2225368
- 负责人:
- 金额:$ 40万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2022
- 资助国家:美国
- 起止时间:2022-09-01 至 2025-08-31
- 项目状态:未结题
- 来源:
- 关键词:
项目摘要
The amount of ambient radio frequency (RF) energy, such as those from Wi-Fi and Bluetooth transmitters, is continuing to increase due to the proliferation of internet-of-things (IoT) devices in our environment. However, the underlying technological challenges have hindered the effective combination of energy from multiple transmitters by using distributed beamforming to harvest useful RF energy for a remote IoT device. This project aims to overcome these technological challenges to develop a high-efficiency distributed beamforming technique to combine energy from multiple RF transmitters and direct it to a remote IoT energy receiver. The project also aims to develop a high-efficiency RF-to-DC converter circuit. It will enable a new technique for harvesting RF energy which will be useful for IoT, biomedical, and remote sensing applications. These techniques are transformative for harvesting RF energy with beamforming capability at ultra-low power levels. The research outcomes from this project will be integrated with a graduate-level curriculum offering, a power management integrated circuits (PMIC) course. All designs and results of this project will be made public on the project website. This project will also engage undergraduate and high school students through a high school summer internship program and the Northeastern University’s Undergraduate Program for Leaders In Future Transformation (UPLIFT) program. The project team will work with the College of Engineering Multi-Cultural Engineering program to increase the diversity of students engaged in NSF Research Experiences for Undergraduates (REU) program. The graduate and undergraduate students participating in this project will be trained on semiconductor chip design. This project aims to develop a high-efficiency distributed beamforming-based RF energy harvesting technique that combines energy from multiple RF energy transmitters and directs it toward a remotely located energy receiver. Effective distributed beamforming requires closed-loop optimization between energy transmitters and the energy receiver. However, the overhead power consumption of sensing and communication needed to realize closed-loop optimization render conventional distributed beamforming techniques inefficient. To overcome the overhead power consumption of communication, this project will develop a new backscatter communication method. The backscatter communication system will enable an ultra-low-power feedback technique for closed-loop optimization. For sensing phase and frequency offset among energy transmitters, a new ultra-low-power energy detection-based sensing platform will also be developed. The project also aims to develop a new RF-to-DC rectifier topology to enable high-efficiency RF energy harvesting across a wide range of received power levels. Accompanying the RF-to-DC converter design will be a maximum power tracking scheme that will provide output impedance matching to realize maximum efficiency operating point for the rectifier. The combination of beamforming, high-efficiency RF-to-DC conversion, ultra-low-power sensing, and backscattering communication will enable a significant increase in RF energy harvesting. The project also includes development of an RF energy transfer protocol to be implemented in wireless networks. A hardware demonstration of the proposed solutions will be carried out using test chips of the energy harvesting system.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
由于物联网(IoT)设备在我们的环境中的扩散,环境射频(RF)能量(例如来自Wi-Fi和蓝牙发射器的RF能量)的量正在持续增加。然而,潜在的技术挑战阻碍了通过使用分布式波束成形为远程物联网设备收集有用的RF能量来有效组合来自多个发射器的能量。该项目旨在克服这些技术挑战,开发一种高效的分布式波束成形技术,将来自多个RF发射器的联合收割机能量结合起来,并将其引导到远程物联网能量接收器。该项目还旨在开发一种高效的RF到DC转换器电路。它将实现一种用于收集RF能量的新技术,这将对物联网,生物医学和遥感应用有用。这些技术对于以超低功率水平收集具有波束成形能力的RF能量是变革性的。该项目的研究成果将与研究生课程,电源管理集成电路(PMIC)课程相结合。该项目的所有设计和成果将在项目网站上公开。该项目还将通过高中暑期实习计划和东北大学未来转型领导者本科生计划(UPLIFT)计划吸引本科生和高中生。该项目团队将与工程学院多元文化工程项目合作,以增加参与NSF本科生研究经验(REU)项目的学生的多样性。参加本项目的研究生和本科生将接受半导体芯片设计方面的培训。该项目旨在开发一种高效的基于分布式波束成形的RF能量收集技术,该技术将来自多个RF能量发射器的能量结合起来,并将其引导到远程能量接收器。有效的分布式波束成形需要能量发射器和能量接收器之间的闭环优化。然而,实现闭环优化所需的感测和通信的开销功耗使得传统的分布式波束成形技术效率低下。为了克服通讯的额外耗电,本计画将发展一种新的反向散射通讯方式。反向散射通信系统将实现用于闭环优化的超低功率反馈技术。为了检测能量发射器之间的相位和频率偏移,还将开发一种新的基于超低功耗能量检测的传感平台。该项目还旨在开发一种新的RF到DC整流器拓扑,以实现在各种接收功率水平下的高效RF能量收集。伴随着RF到DC转换器的设计将是一个最大功率跟踪方案,将提供输出阻抗匹配,以实现整流器的最大效率工作点。波束成形、高效RF到DC转换、超低功耗感测和反向散射通信的组合将使RF能量收集显著增加。该项目还包括在无线网络中实施的RF能量传输协议的开发。该奖项反映了NSF的法定使命,并通过使用基金会的知识价值和更广泛的影响审查标准进行评估,被认为值得支持。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
数据更新时间:{{ journalArticles.updateTime }}
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
数据更新时间:{{ journalArticles.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ monograph.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ sciAawards.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ conferencePapers.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ patent.updateTime }}
Aatmesh Shrivastava其他文献
Aatmesh Shrivastava的其他文献
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
{{ truncateString('Aatmesh Shrivastava', 18)}}的其他基金
CAREER: An Ultra-low Power Analog Computing Hardware Design Framework for Machine Learning Inference in Edge Biomedical Devices
职业:用于边缘生物医学设备中机器学习推理的超低功耗模拟计算硬件设计框架
- 批准号:
2144703 - 财政年份:2022
- 资助金额:
$ 40万 - 项目类别:
Continuing Grant
Energy and Activity Analysis based On-chip methods for Mitigating Denial-of-Sleep Attacks in Ultra-low Power IoT Devices
基于能量和活动分析的片上方法,用于减轻超低功耗物联网设备中的拒绝睡眠攻击
- 批准号:
2125222 - 财政年份:2021
- 资助金额:
$ 40万 - 项目类别:
Standard Grant
CSR: Small: Ultra-Low Power Analog Computing and Dry Skin-Electrode Contact Interface Design Techniques for Systems-On-A-Chip with EEG Sensing and Feature Extraction
CSR:小型:具有 EEG 传感和特征提取功能的片上系统的超低功耗模拟计算和干皮肤电极接触接口设计技术
- 批准号:
1812588 - 财政年份:2018
- 资助金额:
$ 40万 - 项目类别:
Standard Grant
相似国自然基金
Graphon mean field games with partial observation and application to failure detection in distributed systems
- 批准号:
- 批准年份:2025
- 资助金额:0.0 万元
- 项目类别:省市级项目
相似海外基金
CAREER: Verifying Security and Privacy of Distributed Applications
职业:验证分布式应用程序的安全性和隐私
- 批准号:
2338317 - 财政年份:2024
- 资助金额:
$ 40万 - 项目类别:
Continuing Grant
CRII: AF: The Impact of Knowledge on the Performance of Distributed Algorithms
CRII:AF:知识对分布式算法性能的影响
- 批准号:
2348346 - 财政年份:2024
- 资助金额:
$ 40万 - 项目类别:
Standard Grant
Collaborative Research: AF: Medium: The Communication Cost of Distributed Computation
合作研究:AF:媒介:分布式计算的通信成本
- 批准号:
2402836 - 财政年份:2024
- 资助金额:
$ 40万 - 项目类别:
Continuing Grant
Collaborative Research: OAC Core: Distributed Graph Learning Cyberinfrastructure for Large-scale Spatiotemporal Prediction
合作研究:OAC Core:用于大规模时空预测的分布式图学习网络基础设施
- 批准号:
2403312 - 财政年份:2024
- 资助金额:
$ 40万 - 项目类别:
Standard Grant
Collaborative Research: An Integrated Framework for Learning-Enabled and Communication-Aware Hierarchical Distributed Optimization
协作研究:支持学习和通信感知的分层分布式优化的集成框架
- 批准号:
2331710 - 财政年份:2024
- 资助金额:
$ 40万 - 项目类别:
Standard Grant
Collaborative Research: An Integrated Framework for Learning-Enabled and Communication-Aware Hierarchical Distributed Optimization
协作研究:支持学习和通信感知的分层分布式优化的集成框架
- 批准号:
2331711 - 财政年份:2024
- 资助金额:
$ 40万 - 项目类别:
Standard Grant
Next-Generation Distributed Graph Engine for Big Graphs
适用于大图的下一代分布式图引擎
- 批准号:
DP240101322 - 财政年份:2024
- 资助金额:
$ 40万 - 项目类别:
Discovery Projects
New, easy to use, low-cost technologies based on DNA origami biosensing to achieve distributed screening for AMR and improved antibiotic prescribing
基于 DNA 折纸生物传感的易于使用、低成本的新型技术,可实现 AMR 的分布式筛查并改进抗生素处方
- 批准号:
MR/Y034481/1 - 财政年份:2024
- 资助金额:
$ 40万 - 项目类别:
Research Grant
CAREER: Green Functions as a Service: Towards Sustainable and Efficient Distributed Computing Infrastructure
职业:绿色功能即服务:迈向可持续、高效的分布式计算基础设施
- 批准号:
2340722 - 财政年份:2024
- 资助金额:
$ 40万 - 项目类别:
Continuing Grant














{{item.name}}会员




