Efficient usage of the limited natural resources is one of society’s greatest challenges. Just like petroleum and coal, the natural frequency spectrum is limited and needed to be used more efficiently in order not to use up all. It is apparent that current static frequency allocation schemes cannot accommodate demands of the rapidly increasing number of higher data rate devices. Therefore, dynamic
usage of the spectrum must be distinguished from the static usage to increase the availability of frequency spectrum. For this purpose, cognitive radio is proposed as a new technology that provides optimum satisfaction of user requirements like effective spectrum usage. Inconsistent transmission scheme of primary users with not fully occupied licensed bands in frequency, time and space led to a more sophisticated and structured manner - cognitive radio that is aware of its environmental, internal state, and location, and autonomously adjusts its operations to achieve designed objectives. With another way of saying, cognitive radio first senses its spectral environment over a wide frequency band, then adapts the parameters to maximize spectrum efficiency while co-existing with legacy wireless networks. This project only focuses on the spectrum sensing in cognitive radio. Several Spectrum Sensing Methods proposed in the literature are theoretically analysed and interpreted in the sense of advantages and drawbacks. There are generally five signal detection methods. Matched Filtering
2. Energy Detection
3. Cyclostationary Feature Detection
4. Other Methods:
-Higher Order Statistics
-Waveform based sensing
