An iterative multiple primary users localization algorithm based on clustering

Multiple co-channel primary users (PU) existing simultaneously is very common in cognitive radio environments. With the knowledge of the location information of PUs, the cognitive radio can use spectrum-access opportunities more effectively and provides more value-added services. A novel multiple PUs localization algorithm was proposed, which seeks non-cooperative PUs' position by executing k-mean clustering and iterative operations. Simulation results show that the proposed method achieves better performance than traditional expectation-maximization(EM) algorithm.