Intelligent Algorithms for Spectrum Sensing in Cognitive Radio

Frequency spectrum is scared resource and efficient use of it can easily fulfil the need of future applications. But its efficient use is not possible within the existing system, where the allocation of spectrum is done based on fixed spectrum access policy that causes under use of spectrum. For efficient utilization of spectrum new inventive techniques are needed. Using Dynamic spectrum access (DSA) policy we can manipulate the available spectrum. For this purpose Cognitive radio (CR) is a attractive solution to the spectral congestion problem by introducing strategic use of the frequency bands that are not heavenly occupied by licensed users. This paper presents the study of different algorithms for spectrum sensing techniques of cognitive radio networks (CRN). As we know CR is a form of wireless communication which detects vacant spectrums occupies it and avoids the busy one. However to detect vacant spectrum we use the spectrum sensing techniques and CR are known for their transfer values and rate of recognition of the secondary nodes. The problem with the CR is the maximum consumption of energy, so it prevents the system from the high consumption of power utilization.