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

无线产业正在进入一个前所未有的时代，其特征是载波频率和信道带宽都出现了数量级的增长。包括宽信道带宽、自适应定向天线和密集蜂窝部署在内的关键功能将使未来的无线系统快速扩展功能。虽然毫米波频率提供了更高的无线数据速率，但对无线认知、全息通信、虚拟/增强现实、自动驾驶和无线回程等新兴应用的日益增长的需求需要更高的数据速率，而不是5G网络所能提供的。要实现约100 Gbps或更高的数据速率，必须探索超过100 GHz的亚太赫兹和太赫兹频率。这些频率范围提供了丰富的可用频谱，实现了更宽带宽的射频(RF)通道和数据速率能力的下一次飞跃。该项目旨在通过解决极宽带、高方向性信道中的基本挑战来利用亚太赫兹频率的潜力。具体地说，该项目专注于宽带多载波系统在存在极宽带宽引起的波束斜视的情况下的混合波束形成设计。它还研究了密集和定向太赫兹环境中的联合用户与基站和可重构智能表面(RISS)的关联。此外，该项目还探索了启用太赫兹的厘米精度定位功能的使用，从而实现了更精确和灵活的波束形成，以及针对移动设备的增强的关联和切换机制。为了实现这些目标，将在算法设计中使用优化和深度学习技术。此外，该项目将涉及使用由频道探测仪获得的太赫兹信号的测量来模拟真实环境中的虚拟发射器和接收器位置。这些测量将有助于校准纽约大学光线追踪器，并为算法评估提供有价值的数据。在无线网络上使用RISS和精确时间协议将促进基于THz的实时精确定位能力。结合实际的亚太赫兹信道测量和发射器、接收器和RISS的位置位置信息，将提供额外的见解，以增强设计算法的性能。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

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.