Cyclostationary Based Spectrum Sensing in Cognitive Radio: Windowing Approach
Jayanta Mishra1, Deepak Kumar Barik2, Ch. Manoj Kumar Swain3
1Jayanta Mishra, M.Tech Scholar, Department of Electronic and Communication Engineering, Centurion University of Technology & Management (CUTM), Bhubaneswar Campus, Bhubaneswar (Odisha), India.
2Deepak Kumar Barik, Assistant Professor, Department of Electronic and Communication Engineering, Centurion University of Technology & Management (CUTM), Bhubaneswar Campus, Bhubaneswar (Odisha), India.
3Ch. Manoj Kumar Swain, Research Scholar, Department of Electrical Engineering, National Institute of Technology (NIT), Rourkela (Odisha), India.
Manuscript received on 20 March 2014 | Revised Manuscript received on 25 March 2014 | Manuscript published on 30 March 2014 | PP: 95-100 | Volume-3 Issue-1, March 2014 | Retrieval Number: A1014033114/2014©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: A key challenge in operating cognitive radios (CRs) in a self-organizing (ad hoc) network is how to adaptively and efficiently allocate transmission powers and spectrum among CRs according to the surrounding environment. The growing demand of wireless applications has put a lot of constraints on the usage of available radio spectrum which is limited and precious resource. However, a fixed spectrum assignment has lead to under utilisation of spectrum as a great portion of licensed spectrum is not effectively utilised. Cognitive radio is a promising technology which provides a novel way to improve utilisation efficiency of available electromagnetic spectrum. Spectrum sensing helps to detect the spectrum holes (underutilised bands of the spectrum) providing high spectral resolution capability. In this paper cyclostationary feature based spectrum sensing technique is discussed along with the implementation of different window techniques. Cyclostationary feature can be used for spectrum sensing in a very low SNR environment.
Keywords: Cognitive radio networks, Spectrum sensing, Cyclostationary feature based spectrum sensing, Window technique.
Scope of the Article: Computer Science and Its Applications