SPECTRUM SENSING IN CONGNITIVE RADIO NETWORKS

Abstract

Recent research shows that more than 70% of the available spectrum is not utilized efficiently. The bandwidth becomes expensive due to a shortage of frequencies. Therefore for efficient utilization of spectrum, we need to sniff the spectrum to determine whether it is being used by primary user or not. The term cognitive radio refers to the adoption of radio parameters using the sensed information of the spectrum. There are various spectrum sensing techniques proposed in the literature but still there is room for researchers in this field to explore more sophisticated approaches. There are three major categories of spectrum sensing techniques; transmitter detection, receiver detection and interference temperature detection. This thesis presents a survey of techniques suggested in the literature for spectrum sensing with a performance analysis of transmitter-based detection techniques. An algorithm for minimizing sensing time has been proposed in which under high SNR values we can minimize sensing time. Its results are also reliable in comparison with other transmitter detection techniques. A Fuzzy based technique for primary user detection has also been proposed. In comparison with transmitter detection techniques Fuzzy based detection provides good results under low SNR values at the cost of increased in computation time. All simulations are done in MATLAB.