Different spectrum decision methods in a Cognitive radio network were analyzed in this paper. The technology of Cognitive Radio networks needs to make a decision which spectrum band is the best among the available free bands. Spectrum decision is closely related to all operational parameters, channel characteristics and any activity of primary users. Also, spectrum decision depends on all cognitive users inside network activities.
In this paper considered the cognitive radio (CR) networks with the GSM network like primary network cooperation possibility. The cognitive radio system meant radio with a self-management mechanism with different levels of ability to adapt to the changing radio environment. The self-management mechanism is based on the principles of learning and artificial intelligence. In world practice, the frequency assigned to a particular entity in a certain area on a long term basis. However, most commonly frequency for this designated area not always used, and as necessary.
In this paper considered spectrum sensing methods for cognitive radio that based on energy detection. The periodogram method is a DFT based method to estimate power spectral density (PSD). The name of the periodogram comes from the fact that it was first used in determining possible hidden periodicities in time series. The analysis of statistical properties of the periodogram shows its poor quality as an estimator of the PSD. The bias and variance are often used as measures to characterize the performance of an estimator.
In this paper considered spectrum mobility techniques for cognitive radio that based on spectrum sensing. The technology of cognitive radio allows the secondary unlicensed cognitive users to use the spectrum when it is not occupied by the primary users. Due to the randomness of the appearance of primary users, disruptions to both licensed and unlicensed communications are difficult to prevent, so may lead to a low capacity of both licensed and unlicensed communications.