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

• 批准号: 2225576
• 负责人: Duy Nguyen
• 金额: $ 29.99万
• 依托单位: San Diego State University Foundation
• 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=2225576&HistoricalAwards=false
• 关键词: Collaborative; Research; NSF; AoF; CIF

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段中可用的频谱有限，超 5G 无线系统预计将利用太赫兹频段 (0.3-3 THz) 中的大量可用带宽。这将需要在发射器和接收器处使用非常大的天线阵列，以补偿这些高频信号的强烈衰减和缺乏穿透性。然而，扩展现有射频技术以在大带宽上运行变得极其复杂、昂贵，并且需要高功耗。因此，需要彻底简化射频架构；例如，当在大频率和天线尺寸上运行时，数据转换器分辨率的牺牲将是不可避免的。该合作项目解决了与使用带有连接到每个天线的数字接收器的超大型阵列以及采用低分辨率模数/数模转换器相关的理论和实践挑战。它的目的是实现该技术彻底改变太赫兹通信物理层的潜力。该项目采用整体方法，涵盖分析研究、信号处理方法和网络协议，并利用优化、机器学习和贝叶斯推理的严格工具。此外，它将促进参与的美国和芬兰机构之间的研究合作，并支持多元化的博士、硕士和本科生在超 5G/6G 系统关键技术方面的跨学科发展。该项目将解决与超 5G 系统中节能太赫兹通信相关的基本物理层挑战，并分为四个相互关联的主旨： i) 具有低分辨率 ADC/DAC 的双大规模多输入多输出 (MIMO) 系统的两端链路，重点关注信道估计、性能分析、（符号级）预编码和解码设计以及硬件非线性； ii) 真实阵列和射频模型下的空间 Sigma-Delta 处理，结合二维空间采样并仔细表征天线相互耦合和带外发射； iii) 初始接入协议，以促进全数字架构的实际实施，重点关注同步信号设计和信噪比调谐方案； iv) 将变分贝叶斯推理应用于低分辨率 ADC 的信道估计和数据检测，以代替快速时变环境中的传统机器学习模型。通过展示将工作频率推向太赫兹领域的潜力和可行性，该项目将刺激跨学科研究工作，鼓励低复杂性和可控天线架构的技术进步，并实现具有高数据速率和低延迟的新无线应用该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Deep Learning for Estimation and Pilot Signal Design in Few-Bit Massive MIMO Systems

少比特大规模 MIMO 系统中估计和导频信号设计的深度学习

• DOI: 10.1109/twc.2022.3193885
• 发表时间: 2023-01
• 期刊: IEEE Transactions on Wireless Communications
• 影响因子: 10.4
• 作者: Nguyen, Ly V.;Nguyen, Duy H.;Swindlehurst, A. Lee
• 通讯作者: Swindlehurst, A. Lee

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

使用低分辨率 ADC 进行 MIMO 检测的变分贝叶斯视角

• DOI: 10.1109/ieeeconf56349.2022.10052059
• 发表时间: 2022-01
• 期刊: and Computers
• 作者: Nguyen, Ly V.;Swindlehurst, A. Lee;Nguyen, Duy H.N.
• 通讯作者: Nguyen, Duy H.N.

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: 2022-10
• 期刊: and Computers
• 作者: Nguyen, Ly V.;Ngo, Hien Quoc;Tran, Le;Swindlehurst, A. Lee;Nguyen, Duy H.
• 通讯作者: Nguyen, Duy H.