Iterative grid search for RSS-based emitter localization

In this paper, we present a reduced complexity iterative grid-search technique for locating non-cooperating primary emitters in cognitive radio networks using received signal strength (RSS) measurements. The technique is based on dividing the search space into a smaller number of candidate subregions, selecting the best candidate that minimizes a cost function and repeating the process iteratively over the selections. 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. We also look at the performance of our algorithm when the initial search space is specified based on two different data-aided approaches using sensor measurements. Our simulation results show that the data-aided initialization schemes do not provide performance improvement over blind initialization.