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Dictionary learning-based beamspace channel estimation in millimeter-wave massive mimo systems with a lens antenna array
(Institute of Electrical and Electronics Engineers Inc., 2019)
Recent research considers the application of a lens antenna array in order to provide efficient beam selection in beamspace massive MIMO. Achieving the advantages of this beam selection paradigm requires efficient channel ...
Sparse coding with enhanced atom selection for FDD massive MIMO channel estimation
(Institute of Electrical and Electronics Engineers Inc., 2021)
In sparse coding-based channel estimation, atom selection is based on jointly minimizing the sparsity and the error of the representation of the noisy measurement. However, this selection is not necessarily optimal in terms ...
Exploiting sparsity recovery for compressive spectrum sensing: A machine learning approach
(Institute of Electrical and Electronics Engineers Inc., 2019)
Sub-Nyquist sampling for spectrum sensing has the advantages of reducing the sampling and computational complexity burdens. However, determining the sparsity of the underlying spectrum is still a challenging issue for this ...
Primary user emulation and jamming attack detection in cognitive radio via sparse coding
(Springer, 2020)
Cognitive radio is an intelligent and adaptive radio that improves the utilization of the spectrum by its opportunistic sharing. However, it is inherently vulnerable to primary user emulation and jamming attacks that degrade ...
Using OMP and SD algorithms together in mm-Wave mMIMO channel estimation
(Springer London Ltd, 2022)
Lens antenna array is considered as an effective beam selection mechanism in millimeter wave massive multiple input multiple output systems. Efficient channel estimation (CE) algorithms are required to use the advantage ...