SNR Estimation in Communication Systems Using Cognitive Radio

The fast and great developments of communication systems especially on wireless communication lead to big responsibilities on engineers to design systems have the ability for signal to noise ratio (SNR) estimation at the receivers. These developments as a result, must be parallel with solving the problems occurred during receiving the signals. The study and evaluation of digital communication systems by means of SNR at very low SNR environments and how to estimate and predict their values is very attractive topic using cognitive radio (CR). When the data rate is increased at higher order modulation schemes, estimation and prediction of the signal from noisy signal will be very difficult. This paper basically study and survey the most important key parameters needed through the analysis of SNR measurements tools within the most used techniques for estimation and signal classification. Most of the tools related to the estimation and predication SNR such as the role of Artificial intelligence (AI) are mentioned in this review because it is very helpfully in the performance evaluation of the predication system using detection systems i.e. CR. Different types of channels and their effects on the estimation performance are studied like AWGN and fading channels because of their effects on the reduction of detection probability.