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High Efficiency Distributed Beamforming RF Energy Transfer using a Closed-loop Energy Receiver

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
批准号:
2225368
负责人:
Aatmesh Shrivastava
金额:
$40.0万
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
项目状态:
未结题
起止时间:
2022-09-01 至 2025-08-31

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中文摘要
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英文摘要
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.
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CAREER: An Ultra-low Power Analog Computing Hardware Design Framework for Machine Learning Inference in Edge Biomedical Devices
  • 批准号:
    2144703
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $49.99万
  • 财政年份:
    2022
  • 负责人:
    Aatmesh Shrivastava
  • 依托单位:
Energy and Activity Analysis based On-chip methods for Mitigating Denial-of-Sleep Attacks in Ultra-low Power IoT Devices
  • 批准号:
    2125222
  • 项目类别:
    Standard Grant
  • 资助金额:
    $35.65万
  • 财政年份:
    2021
  • 负责人:
    Aatmesh Shrivastava
  • 依托单位:
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
  • 批准号:
    1812588
  • 项目类别:
    Standard Grant
  • 资助金额:
    $50.0万
  • 财政年份:
    2018
  • 负责人:
    Aatmesh Shrivastava
  • 依托单位:
国内基金
海外基金
Graphon mean field games with partial observation and application to failure detection in distributed systems
  • 批准号:
  • 项目类别:
    省市级项目
  • 资助金额:
    --
  • 批准年份:
    2025
  • 负责人:
    MATHIEULOUROCHLAURIERE
  • 依托单位: