The area of signal processing using sensor arrays to estimate the directions of radio signals has drawn considerable interest in recent years. This is due to the opportunities that this area offers in satisfying the increasing demand of wireless communication networks for higher capacity, larger coverage areas, and lower interference effects. Direction-of-Arrival (DOA) estimation methods based on eigen-value evaluation of the signal covariance matrix are known to have high-resolution capabilities and yield accurate estimates. The MUltiple SIgnal Classification (MUSIC) algorithm is an example of these methods that gained most of the research interest since it uses an accurate data model with a sensor array of arbitrary form. In this talk, we highlight the concept of adaptive antenna arrays, or what is known as smart antennas, and the benefits that they offer for wireless communication systems. The sensor array geometry and the signal model used to develop the DOA estimation algorithm are then presented. Detection of radio signals incident on a uniform linear array of equi-spaced sensors using the MUSIC algorithm is illustrated. Results are presented evaluating the performance of MUSIC by studying the effect of changing parameters related to the signal environment, as well as the sensor array.