Arts & Sciences Events
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Arts & Sciences
[PAST EVENT] CS Colloquium: Cooperative Compressive Sensing for Decentralized Networks
October 3, 2014
3pm
Cooperative Compressive Sensing for Decentralized Networks
Zhi Tian, Michigan Technological University and National Science Foundation
Sparsity that characterizes many natural and man-made signals has been exploited over the years in a broad range of statistical inference and signal representation applications, leading to the recent exciting results on compressed sensing for signal reconstruction at sub-Nyquist rates. This talk will discuss the application of compressive sensing for sparse event detection using energy-constrained wireless sensor networks. The physical phenomena under monitoring exhibit localized features that appear sparsely over a large sensing field, which motivate distributed compressive sensing. Meanwhile, for network scalability and robustness, decentralized information processing is considered, in which no fusion center is employed to centrally process all the sensory data. To solve such a sparsity-cognizant cooperative sensing problem in a decentralized manner, we will utilize iterative consensus optimization to search for the globally optimal solutions, under the constraint that sensors transmit at low power and can communicate with their one-hop neighbors only. We will provide several design options, which entail different tradeoffs in communication costs, convergence speed, and sensor awareness level. Further, we will discuss a related cooperative support detection problem, in which sensors seek to consent on the locations of the nonzero elements, but not the amplitudes. A couple of applications will be highlighted, including cooperative spectrum sensing in cognitive radio networks and damage detection in structural health monitoring.
Biography: Zhi (Gerry) Tian is a Professor at the Department of Electrical and Computer Engineering, Michigan Technological University. Her general interest lies in signal processing for communications. Current research focuses on cognitive radio networks and distributed wireless sensor networking. She is an IEEE Fellow, and has served as Associate Editor for IEEE Transactions on Wireless Communications and IEEE Transaction on Signal Processing. Since November 2011, she has been on leave from academia to serve as a Program Director in the Division of Electrical, Communications and Cyber Systems (ECCS) at NSF. Her program portfolios at NSF include communications, sensing and signal processing, and computation and data-enabled science and engineering.
Zhi Tian, Michigan Technological University and National Science Foundation
Sparsity that characterizes many natural and man-made signals has been exploited over the years in a broad range of statistical inference and signal representation applications, leading to the recent exciting results on compressed sensing for signal reconstruction at sub-Nyquist rates. This talk will discuss the application of compressive sensing for sparse event detection using energy-constrained wireless sensor networks. The physical phenomena under monitoring exhibit localized features that appear sparsely over a large sensing field, which motivate distributed compressive sensing. Meanwhile, for network scalability and robustness, decentralized information processing is considered, in which no fusion center is employed to centrally process all the sensory data. To solve such a sparsity-cognizant cooperative sensing problem in a decentralized manner, we will utilize iterative consensus optimization to search for the globally optimal solutions, under the constraint that sensors transmit at low power and can communicate with their one-hop neighbors only. We will provide several design options, which entail different tradeoffs in communication costs, convergence speed, and sensor awareness level. Further, we will discuss a related cooperative support detection problem, in which sensors seek to consent on the locations of the nonzero elements, but not the amplitudes. A couple of applications will be highlighted, including cooperative spectrum sensing in cognitive radio networks and damage detection in structural health monitoring.
Biography: Zhi (Gerry) Tian is a Professor at the Department of Electrical and Computer Engineering, Michigan Technological University. Her general interest lies in signal processing for communications. Current research focuses on cognitive radio networks and distributed wireless sensor networking. She is an IEEE Fellow, and has served as Associate Editor for IEEE Transactions on Wireless Communications and IEEE Transaction on Signal Processing. Since November 2011, she has been on leave from academia to serve as a Program Director in the Division of Electrical, Communications and Cyber Systems (ECCS) at NSF. Her program portfolios at NSF include communications, sensing and signal processing, and computation and data-enabled science and engineering.