项目来源

美国国家科学基金(NSF)

项目主持人

Rose Qingyang Hu

项目受资助机构

Virginia Polytechnic Institute and State University

项目编号

2507713

财政年度

2025,2021

立项时间

未公开

项目级别

国家级

研究期限

未知 / 未知

受资助金额

263420.00美元

学科

未公开

学科代码

未公开

基金类别

Standard Grant

关键词

CCSS-Comms Circuits&Sens Sys ; REU SUPP-Res Exp for Ugrd Supp

参与者

未公开

参与机构

VIRGINIA POLYTECHNIC INSTITUTE&STATE UNIVERSITY

项目标书摘要：Next generation wireless communications will need to support heterogeneous devices with different capabilities on communications,computations,and power to deliver applications with various performance demands such as high data rate,low power consumption,and low latency.Massive multiple-input multiple output(MIMO)has been widely considered a compelling technology for achieving high capacity and high spectrum efficiency in the future wireless communication networks.To fully unleash the potential performance gains claimed by massive MIMO communication systems,it is of vital importance to have timely and accurate channel state information(CSI)at the transmitters,especially at the base station side.The main goal of this project is to explore a systematic approach that accelerates the CSI processing by orders of magnitude in massive MIMO communication systems.The project will lay a foundation to enhancing data rate and energy efficiency,spectral efficiency in the next-generation wireless communications.The research efforts associated with the project can have a significant impact on the lightweight artificial intelligence(AI)design for wireless communication systems,which will further improve many application domains,including beyond 5G wireless networks,autonomous machine-to-machine communications,vehicular networks,and Internet-of-Things.The outcomes of the project can foster the transition of our society into the intelligent wireless networking age,where wireless communication systems can provide seamless support to match many different wireless applications for massive network devices and support many services with high computation demands and quality of service needs.Moreover,the Principal Investigators are committed to integrating research and education by introducing emerging computing and lightweight AI in wireless communication systems into the current electrical and computer engineering curricula in the three participating universities.The project will also provide opportunities for students to learn,develop and apply advanced wireless communications,which they would not receive from a traditional B.S.or M.S.curriculum.Meeting the coherence time requirement in massive MIMO systems can be extremely difficult for CSI processing due to the complex traditional model as well as AI model development and inconsistent performance across environments.In this research project,theoretical analysis and performance evaluations will be obtained for novel algorithms designed for 1)optimization on the decompressed feature in the CSI reconstruction process,2)simplifying the AI structures for multi-rate compression and reconstruction,and 3)autonomous CSI reconstruction performance evaluation and AI model update.The optimized features and simplified AI structures can significantly reduce the complexity in terms of floating point operations per second(FLOPs).Thus,the AI implementation can be accelerated by 1 to 2 orders of magnitude without losing reconstruction accuracy for timely CSI processing in massive MIMO communication systems.The systematic methodologies can be readily extended to facilitate many other applications that encounter the similar challenges and present similar needs on reducing latency and computation needs.Furthermore,this research project can greatly promote the understanding in AI-supported massive MIMO systems for better spectrum and power efficiency and will contribute fundamentally to the design of highly efficient machine-to-machine communications that require high level of autonomy.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.

人员信息

Rose Qingyang Hu(Principal Investigator)：rosehu@vt.edu；

机构信息

【Virginia Polytechnic Institute and State University(Performance Institution)】StreetAddress：300 TURNER ST NW,BLACKSBURG,Virginia,United States/ZipCode：240603359；【VIRGINIA POLYTECHNIC INSTITUTE&STATE UNIVERSITY】StreetAddress：300 TURNER ST NW,BLACKSBURG,Virginia,United States/PhoneNumber：5402315281/ZipCode：240603359；

项目主管部门

Directorate for Engineering(ENG)-Division of Electrical,Communications and Cyber Systems(ECCS)

项目官员

Huaiyu Dai(Email：hdai@nsf.gov；Phone：7032924568)