Collaborative Research: CNS Core: Small: Adaptive Smart Surfaces for Wireless Channel Morphing to Enable Full Multiplexing and Multi-user Gains

连接解决方案需要大规模扩展，以支持数据速率和设备数量空前的指数增长。满足这些需求的主要方法是升级基础设施，例如增加具有多个天线的基站和/或升级客户端。遗憾的是，这些方法没有达到它们的目标，因为在实践中，用户和基站之间的信道具有有限的分散性或丰富性来实现空间复用，并且用户在空间域中没有足够的分离。这一建议将塑造信道，以释放无线网络的全部潜力，而不需要以低成本在功率和费用方面更新基站或用户设备。该研究旨在利用智能无源反射面对无线介质进行自适应修改和变形，以实现空间复用增益。基本的想法是使用智能反射器来创建额外的信道分集，以便在反射接收信号之前对其进行处理，以将接收器处的干扰降至最低。这项研究将通信理论、网络系统设计和天线设计中的PI和技术结合在一起，构建可扩展的低成本无线网络。该项目还提出了一项协同教育和推广计划，利用技术工作为本科生和K-12课堂制作令人兴奋的演示。例如，一个基于智能表面的演示将提高当前Wi-Fi设备的数据速率和覆盖范围，将以务实而引人注目的方式向学生介绍工程奇迹，希望增加与STEM相关的教育环境的多样性。该提案将开发能够变形通道的智能表面设计，并开发硬件原型和算法以提供覆盖和多路复用增益，以支持大量用户和指数级增长的数据速率。设计的带有细粒度控制的智能表面将允许我们在优化过程中根据需要改变无线通道或环境，以增加分集和多路复用增益。我们进一步建立了智能曲面布局的理论和算法，并量化了性能和尺寸之间的权衡。我们为基站开发了低开销的信道估计和低时延优化算法，以支持临时信道变化，提高数据速率和连通性。这项拟议的工作将为多用户设置开发理论和算法，以确保智能表面的可扩展性。这项拟议的工作将使第一个低成本、实用的智能表面和算法能够显著提高数据速率，支持高移动性用户。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 connectivity solutions need to scale up massively to support unprecedented exponential growth in data rates and the number of devices. The primary approach to meet the demands has been to upgrade the infrastructure, such as adding base stations with multiple antennas and/or upgrading clients. Unfortunately, these approaches have fallen short of their goal as in practice, the channels between users and base stations have limited scattering or richness to enable spatial multiplexing, and users are not sufficiently separated in the spatial domain. This proposal will shape the channel to unlock the full potential of wireless networks without requiring updating the base station or user device at a low cost in terms of power and expense. The proposed research aims to adaptively modify and morph the wireless medium using smart passive reflector surfaces to materialize the spatial multiplexing gains. The underlying idea is to use smart reflectors to create additional channel diversity to manipulate the received signal before reflecting it to minimize interference at the receivers. The research brings together PIs and techniques from communications theory, networked system design, and antenna design to build scalable and low-cost wireless networks. The project also proposes a synergistic educational and outreach plan that leverages the technical work to build exciting demos for undergraduate and K-12 classrooms. For example, a smart surface-based demo, which increases the data rate and coverage of current Wi-Fi devices, will introduce students to the wonders of engineering in a pragmatic yet compelling way, with the hope of increasing diversity in STEM-related education environments.The proposal would develop smart surface designs capable of morphing the channel, and develop the hardware prototype and algorithms to provide coverage and multiplexing gains to support massive numbers of users and the exponential increase in data rates. The designed smart surface with fine-grained control would allow us to morph the wireless channel or environment to increase the diversity and multiplexing gains as deemed necessary during optimization. We further establish smart surface placement theory and algorithms and quantify the performance-size trade-offs. We develop low-overhead channel estimation and low-latency optimization algorithms for the base station to support temporal channel changes and improve the data rate and connectivity. The proposed effort would develop the theory and algorithms for multi-user setups to ensure scalability with smart surfaces. The proposed work would enable the first low-cost, practical smart surface and algorithms supporting high-mobility users with significant data-rate improvements.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.