SDR implementation of GoF-based spectrum sensing using artificial neural network for cognitive radio.

In today's world, a means to communicate with virtually no loss is highly essential, with innovations in SDR and improvements in cognitive computing, we could achieve a better way of communication than existing ones, and newer algorithms make it less hard to develop and test these systems. The cognitive radio, which allows dynamic allocation of the spectrum, could serve as a viable solution to congestion in the network and paves the way for dynamic spectrum allocation. The Cognitive Radio may be implemented, may vary with location and architecture, but the most common Software-Defined Radio could be converted into Cognitive Radio CR by a simple predictive and decisive algorithm. Here, we aim to analyze one of the techniques that could improve spectrum sensing of SDR implementation of CR. SDRs can tune to any wireless standard with modulation type, bandwidth, and variable carrier frequency; This paper proposes a Goodness of Fit technique to re-enforce and predict better channels for transmission or reception. [ABSTRACT FROM AUTHOR]