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Statistical modeling of propagation channels for Terahertz band
(Institute of Electrical and Electronics Engineers Inc., 2017)
Digital revolution and recent advances in telecommunications technology enable to design communication systems which operate within the regions close to the theoretical capacity limits. Ever-increasing demand for wireless ...
Compressed spectrum sensing using sparse recovery convergence patterns through machine learning classification
(Institute of Electrical and Electronics Engineers Inc., 2019)
Despite the well-known success of sub-Nyquist sampling in reducing the hardware and computational costs of spectrum sensing, it still has the shortcoming of requiring a pre-determined spectrum sparsity level. This paper ...
Spectrum occupancy prediction exploiting time and frequency correlations through 2D-LSTM
(Institute of Electrical and Electronics Engineers Inc., 2020)
The identification of spectrum opportunities is a pivotal requirement for efficient spectrum utilization in cognitive radio systems. Spectrum prediction offers a convenient means for revealing such opportunities based on ...
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 ...