Spectrum hole detection in TV band using ANN model for opportunistic radio communication

Here we propose an artificial neural network (ANN) model for spectrum sensing in TV band specifically for identifying presence of audio signals. The ANN model is trained with parameters which are a combination of cyclostationary and SNR based features like channel capacity, bandwidth efficiency, autocorrelation. The ANN model is trained based on a new decision making factor termed as utilization factor based on the above combination of attributes which lead to a method for detection of spectrum holes. This unique combination of hypotheses tries to remove the disadvantages of energy detection and cyclostationary feature detection technique, which is helpful for opportunistic cognitive radio applications.