Spectrum Sensing In Cognitive Radio Using Matlab
Garima Nautiyal1, Rajesh Kumar2
1Garima Nautiyal, M. Tech. Student, Dept. of Instrumentation & Control Engineering, Graphic Era University, Dehradun, India.
2Dr. Rajesh Kumar, H.O.D & Prof, Dept. of Instrumentation & Control Engineering, Graphic Era University, Dehradun, India.
Manuscript received on May 26, 2013. | Revised Manuscript received on June 17, 2013. | Manuscript published on June 30, 2013. | PP: 529-532 | Volume-2, Issue-5, June 2013. | Retrieval Number: E1896062513/2013©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: The radio frequency spectrum is a scarce natural resource and its efficient use is of the utmost importance. The spectrum bands are usually licensed to certain services, such as mobile fixed broadcast, and satellite, to avoid harmful interference between different networks. Most spectrum bands are allocated to certain services but worldwide spectrum occupancy measurements show that only portions of the spectrum band are fully used. Moreover, there are large temporal and spatial variations in the spectrum occupancy. In the development of future wireless system the spectrum utilization functionalities will play a key role due to the scarcity of unallocated spectrum. Moreover, the trend in wireless communication system is going from fully centralized system into the direction of self-organizing system where individual nodes can instantaneously establish ad hoc networks whose structure can change over time. Cognitive radio, with the capabilities to sense the operating environment, learn and adapt in real time according to environment creating a form of mesh network, are seen as a promising technology. The paper presents an overview of cognitive radio, various spectrum sensing technique used in CR and also describe the state-of-the-art in cognitive radio standards and regulation. In this project we have implemented and analyzed the energy detection technique for spectrum sensing in CR.
Keywords: Cognitive Radio, Spectrum Sensing, Energy Detection, Primary user, Secondary user, Threshold, Probability of detection, Probability of false alarm.