EARS: Collaborative Research: Blind Source Separation with Integrated Photonics
EARS: Collaborative Research: Blind Source Separation with Integrated Photonics
批准号:
1642991
负责人:
Shuangqing Wei
金额:
$7.5万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2016
资助国家:
美国
项目状态:
已结题
起止时间:
2016-10-01 至 2019-09-30
中文摘要
点击翻译按钮获取中文摘要
英文摘要
The radio world, when viewed through a single antenna, appears as a movie with just one pixel. Multi-antenna systems could reveal the complete radio world in hi-def; however, the astounding quantity of data they generate is simply impossible for electronic computers to handle fast enough. At the same time, the signals received by different antennas are largely redundant, so the first step is generally to combine them in an intelligent way that destroys the undesired and redundant information. Optical (i.e. photonic) physics are extremely broadband and have special properties making them well-suited to multi-antenna problems. Signals carried by light can be very efficiently combined, enabling a photonic processor to funnel the signals from many antennas down to just one information-rich signal that is more manageable for the following electronics. One well-known approach for "intelligently" combining signals is called blind source separation (BSS). BSS is the most powerful technique for pulling apart radio signals that have been mixed over the air. In other words, BSS can use statistics to separate an interesting signal from an interfering signal without assuming anything about them. This project will develop a photonic approach to BSS. Combined, photonics and blind source separation could allow radio systems to better understand and share the wireless spectrum.The objective of the proposed research is to develop a blind source separation technique by using an integrated photonics approach, thereby realizing radio-frequency interference cancellation while preserving user privacy. The project's intellectual merit stems from its orthogonal approach to the challenges of radio access, crossing disciplines of optical physics, statistical analysis, and emerging technology. Spectrum monitoring - an important tool for maintaining harmonious spectrum usage - poses a threat to users' privacy. The project will investigate "blind" spectrum monitoring techniques that can discard the signals of law-abiding users without looking at the content of their data. Science services, such as Earth exploration and radio astronomy, could benefit from format-independent techniques for resolving natural signals through the increasingly loud and complex din of man-made wireless communications. Determining how to intelligently discard undesired information presents a novel theoretical challenge. One pillar of the project will be developing algorithms to bridge the gap between optical hardware and statistical analytics by synthesizing multiple measurements of statistical invariants. A strong experimental thrust to design, build, and demonstrate will validate theoretical insights. A project goal will be the development of hardware that is compatible with recent trends in photonic integration and manufacturing. Foundry compatibility is a key step towards eventual products affordable to the general public.
期刊论文(3)
专著(0)
科研奖励(0)
会议论文
Partition of Random Items: Tradeoff between Binning Utility and Meta Information Leakage
随机项的划分:分箱效用和元信息泄漏之间的权衡
DOI:
10.1109/ict.2018.8464913
发表时间:
2018
期刊:
2018 25th International Conference on Telecommunications (ICT
影响因子:
--
作者:
[Bayat, Farhang, Wei, Shuangqing]
通讯作者:
Wei, Shuangqing
Topological and Algebraic Properties of Chernoff Information between Gaussian Graphs
高斯图间切尔诺夫信息的拓扑和代数性质
DOI:
10.1109/allerton.2018.8635946
发表时间:
2018
期刊:
and Computing (Allerton
影响因子:
--
作者:
[Li, Binglin, Wei, Shuangqing, Wang, Yue, Yuan, Jian]
通讯作者:
Yuan, Jian
Algebraic properties of solutions to common information of Gaussian vectors under sparse graphical constraints
稀疏图形约束下高斯向量公共信息解的代数性质
DOI:
10.1109/allerton.2017.8262852
发表时间:
2017
期刊:
and Computing (Allerton
影响因子:
--
作者:
[Moharrer, Ali, Wei, Shuangqing]
通讯作者:
Wei, Shuangqing
Collaborative Research: An Integrated Framework for Learning-Enabled and Communication-Aware Hierarchical Distributed Optimization
-
批准号:2331711
-
项目类别:Standard Grant
-
资助金额:$25.0万
-
财政年份:2024
-
负责人:Shuangqing Wei
-
依托单位:
CIF: Small: Collaborative Research: Security in Dynamic Environments: Harvesting Network Randomness and Diversity
-
批准号:1320543
-
项目类别:Standard Grant
-
资助金额:$16.66万
-
财政年份:2013
-
负责人:Shuangqing Wei
-
依托单位:
海外基金