Techniques of Candidate Cell Selection for Antenna Tilt Adaptation in LTE-Advanced

Active Antenna System (AAS) technology has the capability of deployment options with dynamic capacity provisioning. One of the features of AAS is high flexibility with respect to antenna tilt control via adapting the orientation of the antenna beam, which improves the signal to interference and noise ratio (SINR) performance to satisfy capacity demand in a non-uniform and spatiotemporally varying traffic distribution. Efficient tilt adaptation in capacity optimization requires identifying the dominant interferer cells rather than considering all neighboring cells of a certain target area. In this paper, considering AAS deployment, the performance of tilt optimization driven by heterogeneous user traffic distribution is investigated by applying a tilt optimization algorithm on selected candidate potential interferer cells. In order to identify these interferer cells, a technique called dominant interferer cell identification is proposed, assuming the presence of a high user traffic concentration (traffic hotspot) in a certain location and periodical user measurement reports at the base station. Moreover, by utilizing the periodic report statistics from users a mechanism to make a network aware of the presence of a traffic hotspot (HS) situation is also proposed. Investigations have been conducted using a 3GPP model and Ray tracing based realworld scenarios. Simulation results have shown that the proposed technique gives a reduced number of dominant interferer cells as compared to a default scheme, which considers all the neighboring cells of a cell serving the target area. In addition, it has also shown a significant performance improvement with a reduced set of dominant interferer cells.