Likelihood criteria based co-channel primary transmitters localization algorithm for cognitive radio networks

Over the last decades the cognitive radio networks (CRNs) has gained the attention in order to resolve the issue of spectrum scarcity. CRN provides the capability to access the spectrum on secondary basis without creating harmful interference to the licensed (primary) users. In this process CRN often needs detect the availability of primary transmitters in order to find the access to the spectrum. In this paper, we presents a method for localization of the unknown number of co-channel primary transmitters. It uses the cooperation of spatially distributed secondary users (SUs) for measurements of the net received signal strength (RSS) at their respective locations. The proposed method first estimates the total number of co-channel primary transmitters using likelihood criteria and then it localizes the primary transmitters individually by applying clustering. K-mean clustering algorithm is applied for classifying the measurements to localize the transmitters individually. The performance of the proposed method is shown in terms of detection probability and false alarm probability.