Aug 25, 2012

Compressed Sensing for Communication Systems

Compressed sensing becomes popular in the field of communications.

This week, there was a small and nice conference, APWCS (Asia Pacific Wireless Communications Symposium), in Kyoto University, JAPAN. Researchers and engineers of wireless communications discussed on compressed sensing for communication systems at a special session called Compressed Sensing for Communication Systems. I felt compressed sensing is a powerful tool for a number of problems in communications.

The following is the summary of the session:

S4: Special Session "Compressed Sensing for Communication Systems"
Thursday, August 23, 11:10 - 12:50, Room: Conference Room III
Chair: Kazunori Hayashi (Kyoto University, Japan)

Session Summary: Compressed sensing has drawing much attention in various fields of applications. This is not only because it enables us to obtain an exact solution from an underdetermined linear system under a certain condition on the measurement matrix taking advantage of the sparsity of the solution, but also because the solution can be obtained via computationally efficient algorithms. In this special session, we focus on the communication applications of compressed sensing, such as OFDM systems, network tomography and networked control systems, as well as a brief introduction to compressed sensing. Moreover, we also have a couple  of talks on the problems with  underdetermined systems, where we discuss a possibility to apply compressed sensing to the problems.

S4.1  A Brief Introduction to Compressed Sensing
Kazunori Hayashi (Kyoto University, Japan); Masaaki Nagahara (Kyoto University, Japan)

S4.2  Application of Compressed Sensing to Inter-Symbol Interference Cancellation in OFDM Systems
Masato Saito (University of the Ryukyus, Japan)

S4.3  Path Construction for Compressed Sensing-Based Network Tomography
Kazushi  Takemoto (Osaka University, Japan); Takahiro Matsuda (Osaka University, Japan); Tetsuya Takine (Osaka University, Japan)

S4.4  Sparsity-Promoting Methods in Remote Control Systems
Masaaki Nagahara (Kyoto University, Japan)

S4.5  A Successive Detector with Virtual Channel Detection for Cooperative Multiuser MIMO Systems
Akihito Taya (Kyoto University, Japan); Satoshi Denno (Okayama University, Japan); Koji Yamamoto (Kyoto University, Japan); Masahiro Morikura (Kyoto University, Japan); Daisuke Umehara (Kyoto Institute of Technology, Japan); Hidekazu Murata (Kyoto University, Japan); Susumu Yoshida (Graduate School of Informatics, Kyoto University, Japan)

S4.6  Nested Array and Its Applications
Masashi Tsuji (Tokyo University of Agriculture and Technology, Japan); Takashi Morimoto (Tokyo University of Agriculture and Technology, Japan); Kenta Umebayashi (Tokyo University of Agriculture and Technology, Japan); Yasuo Suzuki (Tokyo University of Agriculture and Technology, Japan)

Related entries:
Compressed sensing meets control systems
Recent papers on compressed sensing for control systems

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