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المؤلفKhalfi B.
المؤلفHamdaoui B.
المؤلفGuizani M.
المؤلفZorba N.
تاريخ الإتاحة2019-11-04T05:19:28Z
تاريخ النشر2018
اسم المنشورIEEE Transactions on Wireless Communications
المصدرScopus
الرقم المعياري الدولي للكتاب1536-1276
معرّف المصادر الموحدhttp://dx.doi.org/10.1109/TWC.2018.2789349
معرّف المصادر الموحدhttp://hdl.handle.net/10576/12261
الملخصThere 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.
راعي المشروعManuscript 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).
اللغةen
الناشرInstitute of Electrical and Electronics Engineers Inc.
الموضوعcompressive sampling
heterogeneous wideband spectrum occupancy
Wideband spectrum sensing
العنوانEfficient spectrum availability information recovery for wideband dsa networks: A weighted compressive sampling approach
النوعArticle
الصفحات2162-2172
رقم العدد4
رقم المجلد17
dc.accessType Abstract Only


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