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CAREER: Scalable and Ubiquitous Millimeter-Wave Wireless Networks

CAREER: Scalable and Ubiquitous Millimeter-Wave Wireless Networks
职业:可扩展且无处不在的毫米波无线网络
批准号:
2238245
负责人:
Omid Abari
金额:
$57.7万
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2023
资助国家:
美国
项目状态:
未结题
起止时间:
2023-10-01 至 2028-09-30

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中文摘要
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英文摘要
Advancement in computing has enabled emerging applications such as telesurgery, online education, robot automation, and digital twins which require high-data-rate, low-latency, and reliable wireless connectivity. Modern wireless networks (such as 5G and 6G) have promised to enable such connectivity. However, these networks have faced two major problems which prevent them from becoming scalable and ubiquitous. First, they have limited coverage. Specifically, to enable high data-rate connectivity, these networks use very high-frequency signals for communications. Unfortunately, these signals experience high path-loss, and also get easily blocked by obstacles, the human body, or walls. Therefore, these networks do not provide reliable high-data-rate links in remote areas, or environments with static or mobile obstacles. Second, their radios consume higher power than lower frequency radios (e.g. WiFi). Hence, devices with limited energy sources (such as sensors with small batteries) cannot benefit from these networks. This project tackles the above problems, enabling high data-rate, low-latency, and reliable wireless connectivity wherever and whenever is needed. Moreover, developing new wireless technology is strategically important for setting the US as the leader in 5G/6G and its applications. The proposed research is interdisciplinary in nature and will have a significant impact on different aspects of the society such as education, smart environment, health, agriculture, and emergency response.The goal of this project is to make millimeter Wave (mmWave) networks scalable and ubiquitous. To achieve this, it develops novel repeaters and surfaces which can extend coverage and reliability of mmWave networks. The design is low-cost and low-power while supporting multiple users and mobility. The project also develops a new scheme enabling energy-constrained devices to harvest energy from mmWave networks, and use it to power up their mmWave radios. The research takes a holistic view, and innovates across all layers of the wireless stack. To this end, the researchers will design and build novel antennas and hardware that enables passive beamforming and steering, novel algorithms that enable low-power link establishment, and networking protocols which enable end-to-end systems. Finally, the system will be integrated into the Smart Home application, to demonstrate its superior capabilities.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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Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis