CNS Core:Small: Attaining Multi-Terabit/sec Wireless Data Rates

在过去的二十年里，尽管在提供无处不在的无线连接方面取得了长足的进步，但目前可用的实际数据速率远远达不到下一代应用程序的要求。这类应用的例子包括沉浸式虚拟现实(VR)，它可以实现远程手术，对自动驾驶车辆的智能进行即时和按需升级以增强安全性，以及将数字视频数据实时备份到拥有众多商业应用的云中。所有这些应用都需要极高的无线数据速率，而目前的任何无线技术都无法提供这种速率。该项目探讨了利用太赫兹频谱来提供这些数据速率的问题。不幸的是，这部分无线电频谱遭受了许多损害，如阻塞和分子吸收。该项目将通过开发新的通信架构和算法来开发新的方法来克服这些挑战。这给社会带来了许多好处，包括实现真正的远程医疗，增强自动驾驶汽车的安全性，以及提供非常高带宽的无线连接，这些连接可以为下一代无线网络中的一系列新应用奠定基础。该提案旨在研究如何在太赫兹频率下利用多输入多输出(MIMO)技术。鉴于太赫兹传播的特殊特性，该提案将使用测量和建模来解决信号传播不良带来的挑战。此外，该提案还将开发适用于太赫兹的新型光纤和混合MIMO技术。研究的具体目标是：对太赫兹下的大规模MIMO系统进行测量建模；在各种类型的信道损伤(如天线受阻和次优间距)的情况下分析MIMO性能；研究太赫兹下的光MIMO和混合MIMO；使用MatLab仿真和模型演示多太比特/秒通信。这项工作的最终结果将包括MIMO、光-MIMO和混合MIMO的太赫兹模型，其中包括一个信道测量数据库。该项目还将制作用于研究不同通信场景的MatLab软件。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。

Over the past two decades, even though considerable progress has been made in providing ubiquitous wireless connectivity, the actual data rates available today fall far short of what is required by next generation applications. Examples of such applications include immersive virtual reality (VR) that can enable remote surgery, instant and on-demand upgrades to the intelligence of self-driving vehicles to enhance safety, and real-time backup to the cloud of digital video data which has numerous commercial applications. All of these applications require extremely high wireless data rates that cannot be delivered by any of the present-day wireless technologies. This project explores the problem of utilizing the terahertz spectrum to provide these data rates. Unfortunately, this part of the radio spectrum suffers many impairments such as blockage and molecular absorption. This project will develop new methods to overcome these challenges by developing novel communication architectures and algorithms. The benefits to society are many including enabling true remote health care, enhancing safety of autonomous vehicles, and providing very high bandwidth wireless connections that can form the basis for a whole class of new applications in future generation wireless networks.This proposal seeks to study how Multiple-Input Multiple-Output (MIMO) techniques can be utilized at terahertz frequencies. Given the specific idiosyncrasies of terahertz propagation, the proposal will use measurements and modeling to address challenges arising from poor signal propagation. In addition, the proposal will develop novel optical and hybrid MIMO technologies for terahertz. The specific objectives for the research are: perform measurements to model Massive MIMO systems for terahertz; analyze MIMO performance given various types of channel impairments such as obstructed antennas and sub-optimal spacing; study optical-MIMO and hybrid MIMO for terahertz; using Matlab simulations and models demonstrate multi-terabit/sec communications. The eventual outcomes of this work will include terahertz models for MIMO, optical-MIMO and hybrid MIMO including a database of channel measurements. The project will also produce Matlab software to study different communication scenarios.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.