A reduced complexity iterative grid search for RSS-based emitter localization

This paper presents a reduced complexity iterative grid-search algorithm for RSS-based localization of non-cooperating primary emitters in cognitive radio networks. The proposed algorithm is initialized with a small number of candidate locations selected uniformly within the region of interest and then the search space is reduced at each iteration around the candidate that maximizes the likelihood function. We evaluate the performance of the proposed algorithm in independent shadowing scenarios and show that the performance closely approaches to that of the full search, particularly at small shadowing spread values with significantly reduced computational complexity.