Can I read Exploiting Wideband Spectrum Occupancy Heterogeneity for Weighted Compressive Spectrum Sensing on EtoBox?

Exploiting Wideband Spectrum Occupancy Heterogeneity for Weighted Compressive Spectrum Sensing by Khalfi, Bassem; Hamdaoui, Bechir; Guizani, Mohsen; Zorba, Nizar is a scholarly article available to read on EtoBox.

What is Exploiting Wideband Spectrum Occupancy Heterogeneity for Weighted Compressive Spectrum Sensing about?

Compressive sampling has shown great potential for making wideband spectrum sensing possible at sub-Nyquist sampling rates. As a result, there have recently been research efforts that aimed to develop techniques that leverage compressive sampling to enable compressed wideband spectrum sensing. These techniques consider homogeneous wideband spectrum where all bands are assumed to have similar PU traffic characteristics. In practice, however, wideband spectrum is not homogeneous, in that different spectrum bands could have different PU occupancy patterns. In fact, the nature of spectrum assignment, in which applications of similar types are often assigned bands within the same block, dictates that wideband spectrum is indeed heterogeneous, as different application types exhibit different behaviors. In this paper, we consider heterogeneous wideband spectrum, where we exploit this inherent, block-like structure of wideband spectrum to design efficient compressive spectrum sensing techniques that are well suited for heterogeneous wideband spectrum. We propose a weighted $\ell_1$-minimization sensing information recovery algorithm that achieves more stable recovery than that achieved by

Author

Khalfi, Bassem; Hamdaoui, Bechir; Guizani, Mohsen; Zorba, Nizar

Published

2018

Language

EN