Machine Learning

Simulation based project to investigate machine learning techniques for spectrum sensing in Cognitive radio networks with moderate complexity and best performance metric. The idea is to allow more license users to use the spectrum for a certain amount of time for optimum spectrum usage because 80% of the time the spectrum is not used effectively,most of it remains [login to view URL] the sensing will allow for unlicensed users to utilize the radio frequency spectrum for [login to view URL] sensing will eliminate spectrum overcrowding which causes interference. The secondary users and primary users are not allowed to [login to view URL] secondary users must sense the spectrum to check idle spaces in the spectrum to [login to view URL] they can use it until the primary/licensed user occupies the same space and they have to vacate the spectrum to give priority to [login to view URL] the SU has to constantly sense the spectrum to detect presence of the PU.