Collaborative Research: SWIFT: Nonlinear and Inseparable Radar And Data (NIRAD) Transmission Framework for Pareto Efficient Spectrum Access in Future Wireless Networks

合作研究：SWIFT：未来无线网络中帕累托高效频谱接入的非线性不可分离雷达和数据 (NIRAD) 传输框架

基本信息

批准号：
2128448
负责人：
Harold Vincent Poor
金额：
$ 25万
依托单位：
Princeton University
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2021
资助国家：
美国
起止时间：
2021-10-01 至 2024-09-30
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2128448&HistoricalAwards=false
关键词：
Collaborative Research SWIFT Nonlinear Inseparable

项目摘要

Communications and radar are two major applications of electromagnetic waves, which convey information to a destination and glean information from the environment, respectively. Historically, the two technologies were developed and operated independently, thus using different frequency spectrum bands and different hardware. Facing a scarcity of wireless spectrum resources due to the explosive growth in wireless applications, the integration of communications and radar enables sharing of spectrum and hardware, thus substantially reducing the cost and resource demands. Meanwhile, due to the lower amount of electromagnetic emissions, interference to other wireless services will also be substantially reduced. When bandwidth is saved due to the integration of communications and radar sensing, more bandwidth can be committed to each transceiver, thus achieving higher data transmission rates and finer sensing precision, or allowing more wireless devices to be able to access the spectrum. These advantages are of considerable value for applications such as Internet of Things (IoT) and cyber physical systems (CPSs), such as unmanned aerial vehicles (UAVs) and aerial access networks (AANs). The project also will fulfill an education role, including K-12 outreach, and undergraduate/graduate level course design. The findings of the proposed research will disseminated to academic and industrial communities.This study devises a nonlinear and inseparable radar and data (NIRAD) transmission scheme, in which the functions of communications and radar sensing are integrated in the same waveform and use the same hardware. In contrast to linearly superimposed communications and radar sensing, the NIRAD scheme integrates both functions in an inseparable manner, thus allow each to fully exploit the resources of the other. When a waveform is transmitted, the electromagnetic wave brings information to the communication receiver; upon reflections, the wave brings back information for radar sensing, thus achieving both functions in the same round of transmission. When the different functions of communications and radar sensing are integrated in the same waveform and hardware, they have conflicting interests, due to their different purposes. This project discloses the trade-off between communications and radar sensing and characterizes it in an economics framework. The NIRAD technique is applicable to various practical systems, such as high-definition maps in autonomous driving, space-terrestrial communications, and reconfigurable intelligent surfaces, by improving the efficiencies of bandwidth, power and hardware. The proposed algorithms and protocols will be tested using software simulations and field experiments based on a 5G testbed.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.

通信和雷达是电磁波的两个主要应用，它们分别将信息传送到目的地和从环境中收集信息。从历史上看，这两种技术是独立开发和运行的，因此使用不同的频段和不同的硬件。面对无线应用爆发式增长导致无线频谱资源紧缺的情况，通信与雷达的融合可以实现频谱和硬件的共享，从而大幅降低成本和资源需求。同时，由于电磁辐射量较低，对其他无线服务的干扰也将大幅减少。当由于通信和雷达感测的集成而节省带宽时，可以为每个收发器分配更多带宽，从而实现更高的数据传输速率和更精细的感测精度，或者允许更多无线设备能够访问该频谱。这些优势对于物联网 (IoT) 和网络物理系统 (CPS) 等应用具有相当大的价值，例如无人机 (UAV) 和空中接入网络 (AAN)。该项目还将发挥教育作用，包括 K-12 推广和本科/研究生水平课程设计。拟议研究的结果将传播给学术界和工业界。本研究设计了一种非线性不可分离的雷达和数据（NIRAD）传输方案，其中通信和雷达感测功能集成在同一波形中并使用相同的硬件。与线性叠加的通信和雷达传感相比，NIRAD 方案以不可分割的方式集成了这两种功能，从而允许双方充分利用对方的资源。当传输波形时，电磁波将信息带到通信接收器；经过反射后，波带回雷达传感信息，从而在同一轮传输中实现这两种功能。当通信和雷达传感的不同功能集成在相同的波形和硬件中时，由于目的不同，它们会产生利益冲突。该项目揭示了通信和雷达传感之间的权衡，并在经济框架中对其进行了表征。 NIRAD技术通过提高带宽、功耗和硬件的效率，适用于各种实际系统，例如自动驾驶中的高清地图、天地通信和可重构智能表面。所提出的算法和协议将使用基于 5G 测试台的软件模拟和现场实验进行测试。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力优点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（3）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Scalable User Rate and Energy-Efficiency Optimization in Cell-Free Massive MIMO

无蜂窝大规模 MIMO 中的可扩展用户速率和能效优化

DOI：
10.1109/tcomm.2022.3194046
发表时间：
2022-09
期刊：
IEEE Transactions on Communications
影响因子：
8.3
作者：
Tuan, H. D.;Nasir, A. A.;Ngo, H. Q.;Dutkiewicz, E.;Poor, H. V.
通讯作者：
Poor, H. V.

Sum-Rate Maximization for RIS-Assisted Integrated Sensing and Communication Systems With Manifold Optimization

通过流形优化实现 RIS 辅助集成传感和通信系统的总速率最大化

DOI：
10.1109/tcomm.2023.3277872
发表时间：
2023-08
期刊：
IEEE Transactions on Communications
影响因子：
8.3
作者：
Shtaiwi, Eyad;Zhang, Hongliang;Abdelhadi, Ahmed;Swindlehurst, A. Lee;Han, Zhu;Poor, H. Vincent
通讯作者：
Poor, H. Vincent

Performance Optimization for Semantic Communications: An Attention-Based Reinforcement Learning Approach

语义通信的性能优化：基于注意力的强化学习方法