Collaborative Research: NSF-AoF: CIF: AF: Small: Energy-Efficient THz Communications Across Massive Dimensions

合作研究：NSF-AoF：CIF：AF：小型：大尺寸的节能太赫兹通信

基本信息

批准号：
2225575
负责人：
Arnold Swindlehurst
金额：
$ 30万
依托单位：
University of California-Irvine
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：
2022-10-01 至 2025-09-30
项目状态：
未结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2225575&HistoricalAwards=false
关键词：
Collaborative Research NSF AoF CIF

项目摘要

Due to the limited spectrum available in the frequency bands currently used for cellular communications, beyond-5G wireless systems are expected to exploit the large amount of bandwidth available in the THz band (0.3-3 THz). This will require the use of very large arrays of antennas at both the transmitter and the receiver to compensate for the strong attenuation and lack of penetration of signals at these high frequencies. However, scaling up existing radio-frequency technologies to operate over large bandwidths becomes exceedingly complex, expensive, and demands high power consumption. Thus, radical simplifications in the radio-frequency architecture are needed; for example, a sacrifice in the resolution of the data converters will be inevitable when operating across massive frequency and antenna dimensions. This collaborative project tackles the theoretical and practical challenges associated with using very large arrays with digital receivers attached to each antenna and that employ low-resolution analog-to-digital/digital-to-analog converters. It aims to realize this technology's potential for revolutionizing the physical layer in THz communications. The project adopts a holistic approach that encompasses analytical studies, signal processing methods, and network protocols and leverages rigorous tools from optimization, machine learning, and Bayesian inference. Furthermore, it will foster the research collaboration between the participating US and Finnish institutions and support the cross-disciplinary development of a diverse cohort of Ph.D., Master's, and undergraduate students in key technologies for beyond-5G/6G systems.This project will address the fundamental physical-layer challenges associated with energy-efficient THz communications in beyond-5G systems and is organized into four interconnected thrusts: i) Doubly massive multi-input multi-output (MIMO) systems with low-resolution ADCs/DACs at both ends of the link, focusing on the channel estimation, performance analysis, (symbol-level) precoding and decoding design, and hardware non-linearities; ii) Spatial Sigma-Delta processing under realistic array and radio-frequency models, incorporating two-dimensional spatial sampling and carefully characterizing the mutual antenna coupling and out-of-band emissions; iii) Initial access protocols to facilitate the practical implementation of fully digital architectures, focusing on synchronization signal design and signal-to-noise ratio tuning schemes; and iv) Variational Bayesian inference applied to channel estimation and data detection with low-resolution ADCs, to be used in lieu of traditional machine learning models in rapidly time-varying environments. By demonstrating the potential and feasibility of pushing the operating frequencies to the THz realm, the project will stimulate cross-disciplinary research efforts, encourage technological advancements in low-complexity and controllable antenna architectures, and enable new wireless applications with high data rates and low latencies.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.

由于当前用于蜂窝通信的频带中可用的频谱有限，因此预计超过5G无线系统将利用THZ频段（0.3-3 THz）中可用的大量带宽。这将需要在发射器和接收器上使用非常大的天线，以补偿这些高频处信号的强大衰减和缺乏信号的渗透。但是，扩展现有的射频技术以在大型带宽上运行变得非常复杂，昂贵，并且需要高功耗。因此，需要在射频体系结构中进行根本简化。例如，在跨大量频率和天线尺寸运行时，数据转换器的分辨率牺牲将是不可避免的。该协作项目解决了与使用非常大的阵列与每个天线相关的数字接收器以及使用低分辨率类似物对数字/数字/数字到数字转换器相关的理论和实用挑战。它旨在实现这项技术在THZ通信中革命的潜力。该项目采用了一种整体方法，该方法包括分析研究，信号处理方法以及网络协议，并利用了优化，机器学习和贝叶斯推断的严格工具。此外，它将促进参与美国与芬兰机构之间的研究合作，并支持在5G/6G系统的关键技术中，多样化的博士学位，硕士和本科生的跨学科发展，这将解决与thz effer-5G互动的thz Systompers：链接的两端的双重分辨率ADC/DAC的双重大规模多输入多输出（MIMO）系统，重点介绍了通道估计，性能分析，（符号级）预编码和解码设计以及硬件非线性； ii）在逼真的阵列和射频模型下的空间Sigma-Delta处理，结合了二维的空间采样，并仔细地表征了相互的天线耦合和带外排放； iii）初始访问协议，以促进完全数字体系结构的实际实施，重点是同步信号设计和信噪比调整计划；和iv）差异贝叶斯推断应用于低分辨率ADC的通道估计和数据检测，以代替迅速时期的环境中代替传统的机器学习模型。通过证明将操作频率推向THZ领域的潜在和可行性，该项目将刺激跨学科的研究工作，鼓励在低复杂性和可控制的天线体系结构方面的技术进步，并启用具有高数据速度的新无线应用，这些奖励均反映了NSF的范围和范围的范围。标准。

项目成果

期刊论文数量（5）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

A Variational Bayesian Perspective on MIMO Detection with Low-Resolution ADCs

DOI：
10.1109/ieeeconf56349.2022.10052059
发表时间：
2022-10
期刊：
2022 56th Asilomar Conference on Signals, Systems, and Computers
影响因子：
0
作者：
Ly V. Nguyen;A. L. Swindlehurst;D. Nguyen
通讯作者：
Ly V. Nguyen;A. L. Swindlehurst;D. Nguyen

Variational Bayes Inference for Data Detection in Cell-Free Massive MIMO

用于无细胞大规模 MIMO 数据检测的变分贝叶斯推理

DOI：
10.1109/ieeeconf56349.2022.10051916
发表时间：
2022
期刊：
and Computers
影响因子：
0
作者：
Nguyen, Ly V.;Ngo, Hien Quoc;Tran, Le-Nam;Swindlehurst, A. Lee;Nguyen, Duy H.
通讯作者：
Nguyen, Duy H.

Deep Unfolding-Enabled Hybrid Beamforming Design for mmWave Massive MIMO Systems

DOI：
10.1109/icassp49357.2023.10096658
发表时间：
2023-06
期刊：
ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
影响因子：
0
作者：
N. Nguyen;Mengyuan Ma;Nir Shlezinger;Y. Eldar;A. L. Swindlehurst;M. Juntti
通讯作者：
N. Nguyen;Mengyuan Ma;Nir Shlezinger;Y. Eldar;A. L. Swindlehurst;M. Juntti

Overlay Cognitive Radio Using Symbol Level Precoding With Quantized CSI

使用带有量化 CSI 的符号级预编码的叠加认知无线电