Spectrum Sensing in Cognitive Radio Networks Using Time–Frequency Analysis and Modulation Recognition

Spectrum sensing is the most important step in the cognitive radio. It involves spectral detection, channel estimation, and channel state prediction. Most of the traditional spectrum sensing techniques are used for narrowband sensing. At the same time, these techniques cannot distinguish the available user either as primary or secondary. Under the fading conditions, these conventional methods give a false alarm. This chapter presents a new wideband sensing algorithm using Time–Frequency Analysis. Using this method, it is possible to visualize entire spectrum scenario at any instant of time. Further, the primary user and secondary user are distinguished by using Modulation Recognition-based Spectrum sensing which is also presented in this chapter. Several realistic cases are also considered to verify the superiority of the above mentioned proposed methods of spectrum sensing.