An Adaptive Spectrum Sensing Model for Cognitive Radio Application
Wasim Arif 1, Dhrubjun Nath Saikia2, S.Baishya3
1Wasim Arif, Department of Electronics and Communication Engineering, National Institute of Technology Silchar, Assam, India.
2Dhrubjun Nath Saikia, BEL India,
3Dr. Srimanta Baishya,, Department of Electronics and Communication Engineering, National Institute of Technology Silchar, Assam, India.
Manuscript received on March 02, 2014. | Revised Manuscript received on March 034, 2014. | Manuscript published on March 05, 2014. | PP: 171-176 | Volume-4 Issue-1, March 2014. | Retrieval Number: E1943113513/2014©BEIESP
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Abstract: The problem of underutilization of spectrum may be solved by allowing the Secondary Users (SU) to use the spectrum allocated to the Primary Users(PU) (license holder of a spectrum band) when they are not using it, without causing any harmful interference to the PUs. Cognitive Radio (CR) technology promises to solve the problem of spectrum underutilization and spectrum crowding. The cognitive users employ their cognitive abilities, to adaptively change the radio parameters as per the radio environment, to communicate, without harming the primary users. In this paper Cyclostationary Feature Detection method has been taken as the detection method as it not only can detect the signal under low SNR but can also detect different features of the signal such as modulation type, carrier frequencies etc.. Energy Detection or radio meter can only detect presence or absence of the primary signal whereas a Matched Filter system requires extensive knowledge about the channel and the signals that are to be identified. The signals exhibiting cyclostationarity includes Spectral Correlation Function which is a data analysis algorithm that measures how the properties of a spectra varies, position to position, in a two dimensional spectral line map . We have proposed an adaptive sensing mechanism for an effective and efficient detection of spectrum hole. The signal SNR is determined in the first phase and appropriate sensing technique is adopted by the system based on the SNR level in the second phase confirming the radio parameters for CR.
Keywords: Cycle Frequency, Cyclic Autocorrelation Function, Cyclostationarity, Spectral Correlation Function, Spectrum Sensing.