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AuthorKhalfi B.
AuthorHamdaoui B.
AuthorGuizani M.
AuthorZorba N.
Available date2019-11-04T05:19:28Z
Publication Date2018
Publication NameIEEE Transactions on Wireless Communications
ISSN1536-1276
URIhttp://dx.doi.org/10.1109/TWC.2018.2789349
URIhttp://hdl.handle.net/10576/12261
AbstractThere have recently been research efforts that leverage compressive sampling to enable wideband spectrum sensing recovery at sub-Nyquist rates. These efforts consider homogenous wideband spectrum, where all bands are assumed to have similar primary user traffic characteristics. In practice, however, wideband spectrum is not homogeneous, in that different bands could present different occupancy patterns. In fact, applications of similar types are often assigned spectrum bands within the same block, dictating that wideband spectrum is indeed heterogeneous. In this paper, we consider heterogeneous wideband spectrum and exploit its inherent block-like structure to design efficient compressive spectrum sensing techniques that are well suited for heterogeneous wideband spectrum. We propose a weighted ?(1) -minimization sensing information recovery algorithm that achieves more stable recovery than that achieved by existing approaches, while accounting for the variations of spectrum occupancy across both the time and frequency dimensions. In addition, we show that our proposed algorithm requires a smaller number of sensing measurements when compared to the state-of-the-art approaches.
SponsorManuscript received December 6, 2016; revised June 6, 2017, September 27, 2017, and November 30, 2017; accepted December 26, 2017. Date of publication January 9, 2018; date of current version April 8, 2018. This work was supported in part by the U.S. National Science Foundation through the NSF Award under Grant CNS-1162296. The associate editor coordinating the review of this paper and approving it for publication was X. Zhou. (Corresponding author: Bassem Khalfi.) B. Khalfi and B. Hamdaoui are with the School of EECS, Oregon State University, Corvallis, OR 97331 USA (e-mail: khalfib@oregonstate.edu).
Languageen
PublisherInstitute of Electrical and Electronics Engineers Inc.
Subjectcompressive sampling
Subjectheterogeneous wideband spectrum occupancy
SubjectWideband spectrum sensing
TitleEfficient spectrum availability information recovery for wideband dsa networks: A weighted compressive sampling approach
TypeArticle
Pagination2162-2172
Issue Number4
Volume Number17


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