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Cognitive Radio Principles and Spectrum Sensing
J. Divya lakshmi1, Rangaiah. L2

1J. Divya lakshmi, ECE Dept, Research Scholar, Raj Rajeswari College of Engg., Bangalore, Karnataka, India.
2Dr. Rangaiah. L, Prof and H.O.D, ECE Dept, RajaRajeswari College of Engg., Bangalore, Karnataka, India
Manuscript received on July 30, 2019. | Revised Manuscript received on August 25, 2019. | Manuscript published on August 30, 2019. | PP: 4094-4103 | Volume-8 Issue-6, August 2019. | Retrieval Number: F8884088619/2019©BEIESP | DOI: 10.35940/ijeat.F8884.088619
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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: Cognitive Radio is an all intelligent radio network that is advancement over the conventional radio. The difference between the traditional radio and cognitive radio is that all the unused frequency spectrum is utilized to the best of available resources in the cognitive setusp unlike the traditional radio. The major advantage of the cognitive radio is that it can detect channels that are available from the spectrum and modify the parameters used for transmission so that the several unused frequencies can be used concurrently. The research conducted on the cognitive radio is in its primitive stages. However, the need of the hour is the detailed surveys and descriptions of the cognitive radio sensing mechanisms. The operating behavior of the radio will also be improved using the cognitive radio. This paper details the sensing and interference mechanisms of the cognitive radio and explains how and why the cognitive setup is far excellent compared to the conventional radios. There are numerous technologies used in the cognitive radio setup such as the Adaptive radio and Software Defined Radio (SDR). The applications of the findings of this paper can be extended to cognitive radio design and implementation. 
Keywords: Cognitive Radio, Radio Spectrum, Radio Transmission, Spectrum Sensing.