Detecting Primary Signals for Efficient Utilization of Spectrum Using Q-Learning (POSTPRINT)

The efficient utilization of underutilized spectrum is the main theme of the current research. The cognitive radio with the help of Q-learning algorithm is used to detect the presence of primary signals and make utilize the spectrum in the absence of primary signals. In this proposed research the Q-learning algorithm helps the cognitive radio to detect the presence of some of the primary signals which could not be detected due to their presence as weak signals and detects as primary signal due to some interference even though no signal is present. Due to failure to detect or false detection of Signals, the spectrum utilization will not be used efficiently. The proposed Q-learning algorithm model identifies previously known signals and learns to detect the signals which otherwise could not be detected and helps for efficient utilization of spectrum. The simulations further confirmed with results obtained through MATLAB gatool.