Location-based services (LBSs) provide information based on location information specified in a query. Queries that support for LBS are called Location-Dependent Queries (LDQ). One such query is the Reverse Nearest Neighbor (RNN) query that returns the objects that have a query object as their closest object. Just like the Nearest Neighbor (NN) queries, the RNN queries appear in many practical applications such as decision support system, continuous referral systems, profile-based marketing, maintaining document repositories, bioinformatics, etc. Thus efficient methods for the RNN queries in database are required. While the RNN is well studied in the traditional wired, disk-based client-server environment, it has not been tackled in a wireless broadcasting environment. The liner property of wireless broadcast media and power conserving requirement of mobile devices make the problem particularly interesting and challenging. In this paper, the issues involved with organizing location dependent data and answering RNN queries on air are investigated. An efficient data organization, called Jump Rdnn-tree, and the corresponding search algorithms are proposed. Performance of the proposed Jump Rdnn-tree and other traditional indexes (enhanced for wireless broadcast) is evaluated using both uniform and skew data. The results show that Jump Rdnn-tree substantially outperforms the traditional indexes.