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RINGS: WISECOM - Wireless Integrated Sensing, Learning and Communication Networks

RINGS：WISECOM - 无线集成传感、学习和通信网络

基本信息

批准号：
2147955
负责人：
Nuria Gonzalez Prelcic
金额：
$ 79.4万
依托单位：
North Carolina State University
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2022
资助国家：
美国
起止时间：
2022-08-01 至 2025-07-31
项目状态：
未结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2147955&HistoricalAwards=false
关键词：
RINGS WISECOM Wireless Integrated Sensing

项目摘要

Future wireless networks will integrate sensing and communication functions. The sensing capabilities can come from the sensors of the devices in the network. The radio communication signal itself can also be used for sensing, especially when operating at high carrier frequencies, with high bandwidths and large antenna arrays. Examples are cellular networks supporting automated vehicles or industrial robots equipped with radar, lidar or cameras. This project advances the fundamental technologies, from a hardware and software perspective, to enable integrated sensing, learning and communication (ISLAC) wireless networks, capable of obtaining and communicating accurate information about the environment, relevant for the users and for the network operation itself. The sensing accuracy provided by these technologies is critical, both to support a given use case, and to enhance the resilience of the network, enabling a fast respond to failures or mis-configurations. The outcomes of this project will improve cellular connectivity for people and devices, by providing higher data rates, with more reliability, in a way that embraces machine learning and the wealth of sensor data also being deployed in such networks. To establish the potential of integrated sensing, learning and communication networks to enhance their own resilience, this project develops: (a) the core enabling technologies for ISLAC networks, including hardware and signal processing algorithms for joint sensing and communications; (b) mathematical tools to measure resilience accounting for the particular propagation features and network operation at millimeter wave (mmWave) and sub-Terahertz (sub-THz) bands; (c) learning strategies that exploit sensing information to improve network adaptability; and (d) user-centric algorithms that exploit sensing information to improve network autonomy and increase. The developed strategies will be evaluated using a framework based on a combination of ray tracing, experimental measurements and models that mix the digital, physical, and virtual worlds. This methodology will enable the evaluation of the developed technologies in several relevant scenarios supported by cellular networks, including automated vehicles, automated factories, and immersive reality settings.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.

未来的无线网络将集成传感和通信功能。感测能力可以来自网络中的设备的传感器。无线电通信信号本身也可以用于感测，特别是当在高载波频率下操作时，具有高带宽和大天线阵列。例如，支持配备雷达、激光雷达或摄像头的自动化车辆或工业机器人的蜂窝网络。该项目从硬件和软件的角度推进基本技术，以实现综合传感、学习和通信（ISLAC）无线网络，能够获得和传达与用户和网络运行本身相关的准确环境信息。这些技术提供的传感精度至关重要，既可以支持给定的用例，又可以增强网络的弹性，从而能够快速响应故障或错误配置。该项目的成果将通过提供更高的数据速率和更高的可靠性来改善人员和设备的蜂窝连接，其方式包括机器学习和传感器数据的丰富性也被部署在此类网络中。为了确定综合传感、学习和通信网络的潜力，以增强其自身的复原力，该项目开发：（a）国际拉丁美洲和加勒比空间网络的核心赋能技术，包括联合传感和通信的硬件和信号处理算法;（B）用于测量弹性的数学工具，该弹性考虑了毫米波（mmWave）和亚太赫兹（sub-THz）下的特定传播特征和网络操作带;（c）利用感测信息来提高网络适应性的学习策略;以及（d）利用感测信息来提高网络自主性和增加的以用户为中心的算法。开发的策略将使用一个框架进行评估，该框架基于光线跟踪，实验测量和混合数字，物理和虚拟世界的模型的组合。该方法将使开发的技术在蜂窝网络支持的几个相关场景中进行评估，包括自动化车辆，自动化工厂和沉浸式现实设置。该奖项反映了NSF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。

项目成果

期刊论文数量（13）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Beamformer Design and Optimization for Joint Communication and Full-Duplex Sensing at mm-Waves

DOI：
10.1109/tcomm.2022.3218623
发表时间：
2022-12
期刊：
IEEE Transactions on Communications
影响因子：
8.3
作者：
Carlos Baquero Barneto;T. Riihonen;S. Liyanaarachchi;M. Heino;N. González-Prelcic;M. Valkama
通讯作者：
Carlos Baquero Barneto;T. Riihonen;S. Liyanaarachchi;M. Heino;N. González-Prelcic;M. Valkama

Optimizing the Deployment of Reconfigurable Intelligent Surfaces in MmWave Vehicular Systems

优化毫米波车载系统中可重构智能表面的部署