Collaborative Research: NSF-AoF: CIF: Small: AI-assisted Waveform and Beamforming Design for Integrated Sensing and Communication
Collaborative Research: NSF-AoF: CIF: Small: AI-assisted Waveform and Beamforming Design for Integrated Sensing and Communication
批准号:
2326622
负责人:
Mojtaba Vaezi
金额:
$25.98万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2024
资助国家:
美国
项目状态:
未结题
起止时间:
2024-01-01 至 2026-12-31
中文摘要
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英文摘要
Communications and sensing have traditionally operated independently, utilizing separate frequency bands and hardware. The integration of these technologies, known as integrated sensing and communication (ISAC), aims to enhance spectral, energy, and cost efficiency. ISAC designs find applications in wireless communications, localization, autonomous vehicles, area imaging, environmental monitoring, and more. However, achieving optimal ISAC designs solely through analytical approaches faces challenges due to performance trade-offs and complexity. To overcome these hurdles, this project employs artificial intelligence (AI) to design such solutions and establish theoretical foundations for ISAC. A unique European collaboration (Finland) unites diverse research expertise, fostering economic, societal, and research impacts. Knowledge transfer occurs through dissemination, curriculum development, student exchanges, and industry collaborations. The project also engages with farmers' markets to showcase ISAC's potential to benefit local agriculture. This project aims to explore the optimal integration of sensing and communications through AI-assisted ISAC designs. The research consists of three interconnected thrusts. The first thrust involves designing unified waveforms, constellations, and beamforming techniques for both sensing and communications. Additionally, AI-based channel learning and generation methods will be developed. The second thrust focuses on implementing ISAC designs using large aperture arrays. The project aims to establish the theoretical foundations of the extended near-field of ISAC channels with electrically large aperture arrays and leverage the unique channel characteristics to optimize integration gains. The third thrust is dedicated to real-time implementation and evaluation of the AI-assisted ISAC designs and algorithms, considering factors such as performance, robustness, and advancement metrics.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: Harnessing Interference with Deep Learning: Algorithms and Large-Scale Experiments
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批准号:2239524
-
项目类别:Continuing Grant
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资助金额:$59.95万
-
财政年份:2023
-
负责人:Mojtaba Vaezi
-
依托单位:
ERI:Interference-Aware Constellation Design
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批准号:2301778
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项目类别:Standard Grant
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资助金额:$19.62万
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财政年份:2023
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负责人:Mojtaba Vaezi
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依托单位:
国内基金
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