ERI: Towards Environment-Aware Wireless Communications for Next Generation Networks

下一代网络预计将提供超低延迟和高速数据速率，以支持医疗沉浸式技术、虚拟/增强现实和智慧城市应用等新技术和应用。为了满足前所未有的宽带接入需求，该项目将利用高分辨率环境传感数据来推断基于位置的信道特性，提前预测链路阻塞，并在动态室内环境中实现稳健的毫米波通信。提出的链路组态算法的系统级设计将被开发和分析。所提出的算法有望增强频谱可用性和室内毫米波无线网络的接入，并使新兴技术应用成为可能。这项研究将在一所主要的本科院校进行，并将通过直接的研究经验，在课堂上影响大量代表性不足的少数民族学生，目的是扩大他们的参与度，提高他们的保留率。研究结果将在科学会议和期刊出版物上传播。该项目的主要目标是在真实的室内环境中实现高速和超可靠的毫米波通信。为了实现这一目标，将开发利用激光雷达和毫米波传感器数据融合的新传输策略。项目总体目标是：(1)设计和开发适用于基于激光雷达和毫米波传感数据的动态室内环境的毫米波系统的低复杂性和延迟链路配置算法；(2)研究利用激光雷达强度数据对常见室内表面进行超视距毫米波通信分类；(3)利用先进的阵列处理和信号处理工具开发适应环境杂波的传输策略；(4)开发基于激光雷达传感的毫米波通信链路早期阻塞预警算法。预期的研究结果将导致新的数据驱动信道模型、信号处理和机器学习方法，以减轻动态环境中毫米波链路配置的挑战。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Next-generation networks are expected to deliver ultra-low-latency and high-speed data-rates to support new technology and applications such as healthcare immersive technology, virtual/augmented reality, and smart city applications. To meet the unprecedented demand for broadband access, this project will leverage high-resolution environment sensory data to infer location-based channel characteristics, predict link blockages beforehand, and enable robust mm-wave communications in dynamic indoor environments. System-level design of the proposed link configuration algorithms will be developed and analyzed. The proposed algorithms are expected to enhance the spectrum usability and access to indoor mm-wave wireless networks and enable emerging technology applications. This research will be conducted at a primarily undergraduate institution and will impact a significant number of underrepresented minority students in the classroom and through direct research experience with the goal of broadening their engagement and promoting their retention. The research findings will be disseminated in scientific conferences and journal publications.The main goal of this project is to enable high-speed and ultra-reliable mm-wave communications in realistic indoor environments. To this achieve this, new transmission strategies that make use of Lidar and mm-wave sensory data fusion will be developed. The overall project objectives are: (1) design and develop low complexity and latency link configuration algorithms for mm-wave systems suitable for dynamic indoor environments based Lidar and mm-wave sensory data; (2) investigate the use of Lidar intensity data for classification of common indoor surfaces for beyond line-of-sight mm-wave communication; (3) leverage advanced array processing and signal processing tools to develop transmission strategies that adapts to environment clutter; and (4) develop early blockage warning algorithms for mm-wave communication links based on Lidar sensing. The expected research findings will lead to new data-driven channel models and signal processing and machine learning approaches that mitigate mm-wave link configuration challenges in dynamic environments.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.