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Collaborative Research: U.S.-Ireland R&D Partnership: CIF: AF: Small: Enabling Beyond-5G Wireless Access Networks with Robust and Scalable Cell-Free Massive MIMO

Collaborative Research: U.S.-Ireland R&D Partnership: CIF: AF: Small: Enabling Beyond-5G Wireless Access Networks with Robust and Scalable Cell-Free Massive MIMO
合作研究:美国-爱尔兰 R
批准号:
2322191
负责人:
Arnold Swindlehurst
金额:
$30.0万
依托单位国家:
美国
项目类别:
Standard 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 2026-09-30

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中文摘要
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英文摘要
In wireless cellular networks, interference between user signals in adjacent cells remains a persistent problem that hinders connectivity at the cell boundaries. A new architecture for wireless networks is emerging that eliminates the concept of cells and relies on a distributed network of access points across a wide area that share data and cooperate to combat interference. This new ``cell-free'' approach has been shown to provide significantly more uniform coverage and data rates comparable to, and in some cases better than, the classical centralized cellular approach. To date, most theoretical studies of cell-free systems have assumed relatively favorable radiowave propagation that leads to good performance using simple linear signal processing methods. This project, by contrast, focuses on less favorable scenarios that require more complicated non-linear statistical methods. The research under the project will be conducted with collaborators from U.S., Irish, and Northern Irish institutions, and will support a diverse cohort of postdocs, PhD, Master's, and undergraduate students in key 5G and 6G technologies. The primary goals of this research are to develop nonlinear statistical inference methods for estimation and detection and devise robust and scalable resource allocation solutions for cell-free massive MIMO under less favorable channel propagation conditions. Project research activities will advance the current state of knowledge on cell-free massive MIMO and are organized into three interconnected thrusts: i) Developing nonlinear variational Bayesian methods for centralized and distributed processing, focusing on channel estimation, data detection, and user activity detection tasks; ii) Developing novel user-centric pilot designs and power control schemes, considering practical challenges in cell-free massive MIMO such as hardware impairments and fronthaul quantization errors; and iii.) Devising robust and scalable resource allocation strategies to resolve the user congestion issue and improve network-wide energy efficiency, considering non-uniform data traffic load conditions. The project's demonstration of the capabilities of robust and scalable cell-free massive MIMO will inspire collaborative and cross-disciplinary research efforts and establish cell-free massive MIMO as a transformative beyond-5G/6G wireless access technology.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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  • 批准号:
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  • 项目类别:
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  • 资助金额:
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