Reliable Recovery of Hierarchically Sparse Signals for Gaussian and Kronecker Product Measurements

@article{Roth2020ReliableRO,
  title={Reliable Recovery of Hierarchically Sparse Signals for Gaussian and Kronecker Product Measurements},
  author={Ingo Roth and M. Kliesch and Axel Flinth and G. Wunder and J. Eisert},
  journal={IEEE Transactions on Signal Processing},
  year={2020},
  volume={68},
  pages={4002-4016}
}
  • Ingo Roth, M. Kliesch, +2 authors J. Eisert
  • Published 2020
  • Computer Science, Mathematics, Physics
  • IEEE Transactions on Signal Processing
  • We propose and analyze a solution to the problem of recovering a block sparse signal with sparse blocks from linear measurements. Such problems naturally emerge inter alia in the context of mobile communication, in order to meet the scalability and low complexity requirements of massive antenna systems and massive machine-type communication. We introduce a new variant of the Hard Thresholding Pursuit (<inline-formula><tex-math notation="LaTeX">$\mathsf{HTP}$</tex-math></inline-formula… CONTINUE READING
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