Exploiting Sparsity Recovery for Compressive Spectrum Sensing: A Machine Learning Approach

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 approach. Along this line, this paper proposes an algorithm for narrowband sp...

Full description

Bibliographic Details
Main Authors: Mahmoud Nazzal, Ali Riza Ekti, Ali Gorcin, Huseyin Arslan
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/8688400/