CIF: Small: Wireless Massive Access: From Fundamental Limits to Practical Design

该项目将开发支持密集部署的无线设备的理论和技术。项目成果将满足对支持物联网(IoT)的新无线技术的迫切需求，物联网可促进医疗保健、交通、智慧城市和公共安全等领域的重要应用。在无线电频谱有限的情况下，关键是设计一个高效的系统来支持无线海量接入，其中许多设备都很小，由电池供电。具体地说，该项目将研究现实假设下无线海量接入的基本限制，并开发接近这些限制的实际设计。该项目通过研究具有大量用户的模型，超越现有的多用户系统理论，推动了通信、信息理论和信号处理的发展。这个项目将集中于两个主要的技术挑战：1.为大量设备的制度下的通信系统开发一种理论。重要的实际问题，如异步性和渠道不确定性，将在根本层面上解决，而不是事后才考虑。2.设计对各种信道不确定性具有弹性的可伸缩码。学习技术将被应用于开发设备特性，以减少不确定性。关键的设计概念将通过软件定义无线电的实验进行评估。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。

This project will develop theory and techniques for supporting densely deployed wireless devices. The project outcome will meet the urgent need for new wireless technologies enabling the Internet of Things (IoT) that facilitates important applications in healthcare, transportation, smart city, and public safety, to name a few. With limited radio spectrum, the key is to design an efficient system to support wireless massive access, where many devices are small and battery-powered. Specifically, this project will study the fundamental limits of wireless massive access under realistic assumptions and develop practical designs that approach those limits.This project pushes the envelope of communications, information theory, and signal processing by studying models with a massive number of users beyond the existing theory for multiuser systems. This project will focus on two main technical challenges: 1. To develop a theory for communication systems in the regime of a massive number of devices. Important practical issues such as asynchrony and channel uncertainties will be addressed at the fundamental level rather than as an afterthought. 2. To design scalable codes that are resilient to various channel uncertainties. Learning techniques will be applied to exploit device idiosyncrasies to reduce uncertainties. Key design concepts will be evaluated through experimentation with software-defined radios.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.