Collaborative Research: Beamforming, User Association and Precise Positioning in Future Terahertz-Enabled Wireless Networks

合作研究：未来太赫兹无线网络中的波束成形、用户关联和精确定位

• 批准号: 2234123
• 负责人: Theodore Rappaport
• 金额: $ 20.52万
• 依托单位: New York University
• 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
• 起止时间: 2023-09-01 至 2026-08-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2234123&HistoricalAwards=false
• 关键词: Collaborative; Research; Beamforming; User; Association

The wireless industry is entering an unprecedented era characterized by orders of magnitude increase in both carrier frequency and channel bandwidth. Key features including wide channel bandwidths, adaptable directional antennas, and dense cell deployments will set future wireless systems on a rapid expansion of capabilities. While mmWave frequencies offer improved wireless data rates, the growing demand for emerging applications like wireless cognition, holographic communications, virtual/augmented reality, autonomous driving, and wireless backhaul necessitates even higher data rates beyond what 5G networks can provide. To achieve data rates of around 100 Gbps or more, it becomes essential to explore frequencies in the sub-THz and THz range, surpassing 100 GHz. These frequency ranges offer abundant available spectra, enabling wider bandwidth radio frequency (RF) channels and the next leap in data rate capabilities. This project aims to leverage the potential of sub-THz frequencies by addressing fundamental challenges in extremely wideband, highly directional channels.Specifically, the project focuses on the design of hybrid beamforming for a wideband multicarrier system in the presence of beam squinting caused by the extremely wide bandwidth. It also investigates joint user association with base stations and reconfigurable intelligent surfaces (RISs) within the dense and directional THz environment. Moreover, the project explores the use of THz-enabled centimeter-accuracy positioning capabilities, enabling more precise and agile beamforming, as well as enhanced association and handover mechanisms for mobile devices. To accomplish these goals, optimization and deep learning techniques will be employed in algorithm design. Furthermore, the project will involve using measurements of THz signals obtained by a channel sounder to emulate virtual transmitter and receiver locations in real-world environments. These measurements will assist in calibrating the NYU ray tracer and provide valuable data for algorithms evaluation. The use of RISs and the Precision Time Protocol over wireless networks will facilitate real-time, THz-based precise position-location capabilities. Incorporating actual sub-THz channel measurements and the position location information of transmitters, receivers, and RISs will provide additional insights to enhance the performance of the designed algorithms.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.

无线行业正在进入一个前所未有的时代，其特征是载体频率和频道带宽的数量级。关键功能在内，包括宽通道带宽，适应性的定向天线和密集的细胞部署将使未来的无线系统迅速扩展功能。尽管MMWave频率提供了提高的无线数据速率，但对无线认知，全息沟通，虚拟/增强现实，自动驾驶和无线回程等新兴应用的需求不断增长，这使得超过5G网络可以提供的更高数据速率。为了达到约100 Gbps或更多GBP的数据速率，探索在Sub-THZ和THZ范围内的频率至关重要，超过100 GHz。这些频率范围提供了丰富的可用光谱，从而实现了更宽的带宽射频（RF）通道和数据速率功能的下一个飞跃。该项目旨在通过解决极端方向通道中的基本挑战来利用Sub-Thz频率的潜力。特别是，该项目的重点是在存在由极宽的带宽引起的宽带多层抛物系统的情况下，用于宽带多层抛光系统的混合边界的设计。它还研究了与基站的联合用户关联，并在密集和定向的环境中进行了可重构智能表面（RISS）。此外，该项目探讨了启用了THZ的厘米准确性定位功能，从而实现了更精确和更敏捷的光束，并增强了移动设备的关联和交换机制。为了实现这些目标，算法设计将采用优化和深度学习技术。此外，该项目将涉及使用通道音响器获得的THZ信号的测量，以模拟现实世界环境中的虚拟发射器和接收器位置。这些测量结果将有助于校准NYU射线示踪剂，并为算法评估提供有价值的数据。在无线网络上使用RISS和精确时间协议将有助于实时，基于THZ的精确位置位置功能。结合实际的Sub-THZ通道测量值以及发射机，接收器和RIS的位置信息将提供其他见解，以增强设计算法的性能。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子优点和更广泛影响的审查标准来通过评估来获得支持的。