ANALYSIS OF SPECTRUM SENSING TECHNIQUES IN COGNITIVE RADIO FOR SPECTRUMS

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ANALYSIS OF SPECTRUM SENSING TECHNIQUES IN COGNITIVE RADIO FOR SPECTRUMS

Abstract:

With the advancement of wireless communications, recent research by the FCC (Federal Communication Commission) shows that large portion of the available licensed spectrum band lies unused, that is only used by licensed users (primary users). The bandwidth becomes expensive due to a shortage of frequencies. Therefore for utilization of the spectrum band, FCC allowed secondary (unlicensed) users to utilize the licensed band without interfering with the primary (licensed) users when it is not in use by the primary user named it as Cognitive Radio. Cognitive Radio (CR) defiefficient ned as:”A radio system employing technology that allows the system: to obtain knowledge of its operational and geographical environment, established policies and its internal state; to dynamically and autonomously adjust its operational parameters and protocols according to its obtained knowledge in order to achieve predefined objectives; and to learn from the results obtained. This thesis work analyses the performance of the energy detector based on MAP for identifying the status of the primary user. Matlab simulation is used for received signal from Cognitive radio networks and energy detector to find whether the spectrum being used or not by the primary user and later thesis tries to establish a relationship between signal-to-noise ratio and the detection of primary user signal by using maximum a posteriori energy detection method. This thesis work also analyzes the spectrum detection schemes based on dynamic threshold algorithm. Spectrum detection based on fixed threshold are sensitive to noise uncertainty, the energy detection and the matched filter detection are analyzed for the case of noise uncertainty and dynamic threshold algorithm and found that energy detection based on dynamic threshold can improve the antagonism of noise uncertainty; get good performance of detection without increasing the computer complexity and improves the detection performance for the schemes that are sensitive to noise uncertainty.

ANALYSIS OF SPECTRUM SENSING TECHNIQUES IN COGNITIVE RADIO FOR SPECTRUMS

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