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 mixedreality 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.