NeTS: Small: Massive Wireless Random Access: Principles and Protocols
NeTS: Small: Massive Wireless Random Access: Principles and Protocols
批准号:
1817205
负责人:
Ayfer Ozgur
金额:
$50.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2018
资助国家:
美国
项目状态:
已结题
起止时间:
2018-10-01 至 2022-09-30
中文摘要
人们普遍预计下一代无线系统将连接大量低能耗传感器和执行器,这些传感器和执行器构成智能技术和网络物理系统的结构。由此产生的“物联网”预计将成为未来十年技术增长的主要驱动力之一。然而,它的设计给无线工程师带来了新的挑战。关键的挑战之一是如何使大量的低能耗无线设备能够以最小的协调和信道估计开销零星地访问稀缺的频谱。虽然有几种现有的随机接入解决方案,但由于重传和载波传感的高能量成本、近距离效应或显著的控制层开销,它们并不适合这种新兴范例。该项目旨在从根本上重新思考物联网网络的无线随机接入,将大量能量严重受限的设备的零星接入作为其关键区别特征。它开发了一个数学框架来研究这个问题,并展示了这个框架是如何与理论计算机科学中一个看似无关的问题——组测试——联系起来的。通过建立这种连接,它旨在开发可转化为创新随机访问协议的最佳数学解决方案,该协议(a)共同优化控制和信息层任务,例如设备发现和数据传输;(b)包含传感器碰撞,从而消除碰撞解决和重传的复杂性和能量成本;(c)设计满足严格的能量约束并与发射机的能量动态相匹配;(d)采用不需要信道估计的简单调制和检测技术;(e)低复杂度(编码/解码),灵活(可应用于异构环境),并且对噪声和设备缺陷具有弹性。公式化问题的多学科性质将使电子工程、计算机科学和应用数学的不同分支学科的思想相互交融。该项目辅以强有力的教育和外展计划,重点是扩大电气工程的参与。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。
英文摘要
The next generation of wireless systems are widely expected to connect a massive number of low-energy sensors and actuators that form the fabric of smart technologies and cyberphysical systems. The resultant 'Internet of Things' is expected to be one of the major drivers of technological growth over the next decade. However, its design presents new challenges to wireless engineers. One of the key challenges is how to enable a massive number of low-energy wireless devices to sporadically access the scarce spectrum with minimal coordination and channel estimation overheads. While there are several existing solutions for random access, they are not well-suited for this emerging paradigm due to high energy cost for retransmissions and carrier sensing, near-far effects, or significant control layer overheads.This project aims to fundamentally rethink wireless random access for IoT networks by identifying the sporadic access of a massive number of severely energy limited devices as its key distinguishing characteristic. It develops a mathematical framework to study this problem and shows how this framework relates to a seemingly unrelated problem in theoretical computer science called group testing. By building on this connection it aims to develop optimal mathematical solutions that can be translated to innovative random-access protocols which (a) jointly optimize control and information layer tasks, such as device discovery and data transmission; (b) embrace sensor collisions and thus, eliminate the complexity and energy cost of collision resolution and retransmissions; (c) are designed to satisfy stringent energy constraints and match the energy dynamics at the transmitters; (d) employ simple modulation and detection techniques that do not require channel estimation; and (e) are low-complexity (encoding/decoding), flexible (can be applied in heterogeneous settings), and resilient to noise and device imperfections. The multi-disciplinary nature of the formulated problems will enable the cross-fertilization of ideas from different sub-disciplines of electrical engineering, computer science and applied mathematics. The project is complemented with a strong education and outreach program with an emphasis on broadening participation in electrical engineering.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.
期刊论文(21)
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DOI:
--
发表时间:
2021
期刊:
Advances in neural information processing systems
影响因子:
--
作者:
[Wei-Ning Chen, Peter Kairouz]
通讯作者:
Wei-Ning Chen, Peter Kairouz
DOI:
10.1109/tit.2019.2951703
发表时间:
2020
期刊:
IEEE Transactions on Information Theory
影响因子:
2.5
作者:
[Inan, Huseyin A., Kairouz, Peter, Ozgur, Ayfer]
通讯作者:
Ozgur, Ayfer
DOI:
10.1109/globecom46510.2021.9685768
发表时间:
2021-12
期刊:
2021 IEEE Global Communications Conference (GLOBECOM)
影响因子:
--
作者:
[Chuan-Zheng Lee;L. P. Barnes;Wenhao Zhan;Ayfer Özgür]
通讯作者:
Chuan-Zheng Lee;L. P. Barnes;Wenhao Zhan;Ayfer Özgür
Adaptive Group Testing on Networks with Community Structure
具有社区结构的网络的自适应分组测试
DOI:
10.1109/isit45174.2021.9517888
发表时间:
2021
期刊:
2021 IEEE International Symposium on Information Theory (ISIT
影响因子:
--
作者:
[Ahn, Surin, Chen, Wei-Nina, Ozgur, Ayfer]
通讯作者:
Ozgur, Ayfer
Breaking The Dimension Dependence in Sparse Distribution Estimation under Communication Constraints
打破通信约束下稀疏分布估计的维数依赖性
DOI:
--
发表时间:
2021
期刊:
Proceedings of Machine Learning Research
影响因子:
--
作者:
[Wei-Ning Chen, Peter Kairouz]
通讯作者:
Wei-Ning Chen, Peter Kairouz
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