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      • Department of Electrical and Electronics Engineering
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      Compressive sampling and adaptive multipath estimation

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      Author
      Pilancı, Mert
      Arıkan, Orhan
      Date
      2010
      Source Title
      2010 IEEE 18th Signal Processing and Communications Applications Conference
      Publisher
      IEEE
      Pages
      260 - 263
      Language
      Turkish
      Type
      Conference Paper
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      Abstract
      In many signal processing problems such as channel estimation and equalization, the problem reduces to a linear system of equations. In this proceeding we formulate and investigate linear equations systems with sparse perturbations on the coefficient matrix. In a large class of matrices, it is possible to recover the unknowns exactly even if all the data, including the coefficient matrix and observation vector is corrupted. For this aim, we propose an optimization problem and derive its convex relaxation. The numerical results agree with the previous theoretical findings of the authors. The technique is applied to adaptive multipath estimation in cognitive radios and a significant performance improvement is obtained. The fact that rapidly varying channels are sparse in delay and doppler domain enables our technique to maintain reliable communication even far from the channel training intervals. ©2010 IEEE.
      Keywords
      Compressed sensing
      Matrix identification
      Sparse multipath channels
      Structured perturbations
      Structured total least squares
      Compressed sensing
      Matrix identification
      Sparse multi-path channel
      Structured perturbations
      Structured total least squares
      Estimation
      Linear systems
      Multipath propagation
      Relaxation processes
      Signal processing
      Signal reconstruction
      Matrix algebra
      Permalink
      http://hdl.handle.net/11693/28473
      Published Version (Please cite this version)
      http://dx.doi.org/10.1109/SIU.2010.5650382
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      • Department of Electrical and Electronics Engineering 3601
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