A reverse nearest neighbor (RNN) search retrieves all points in a given data set whose nearest neighbor is a given query point. It is important for location-based services such as traffic monitoring and enhanced 911 service and mixed-reality games. The reverse nearest neighbor queries appear in many practical situations. Existing algorithms have been proposed recently to support RNN search in the traditional client-server service model. In this paper, we conduct a preliminary study on RNN search in wireless data broadcast environments. We employ three air indexing techniques, namely, a naive air index, Rdnn-tree air index and D-tree air index, and devise algorithms based on these techniques to search RNNs on the air. A simulation is conducted to compare the three air indexing techniques. The result shows that RNN search methods in Rdnn- and D-tree outperform the naive index approach significantly in terms of tuning time.