Inter-site interference distribution acts as a basic limitation on how much performance a network service provider can achieve in an urban network scenario. There are many different ways of controlling this interference levels. One such method is tuning the antenna downtilt depending on the network situation. Antenna downtilt can also be seen as a powerful tool for load balancing in the network. This thesis work involves a study of the impact of the antenna downtilt in an urban environment, involving non-uniform user distribution. A realistic dual ray propagation model is used to model the path gain from the base station to a UE. Such a propagation model is used along with a directional antenna radiation pattern model to calculate the overall path gain from the base station to a UE. Under such modeling, the results of the simulations show that the antenna downtilt plays a crucial role in optimizing the network performance. The results show that the optimal antenna downtilt angle is not very sensitive to the location of the hotspot in the network. The results also show that the antenna downtilt sensitivity is very much dependent on the network scenario. The coupling between the antenna downtilt and the elevation half power beamwidth is also evaluated.

Multiple-input-multiple-output (MIMO) systems of current LTE releases are capable of adaptation in the azimuth only. More recently, the trend is to enhance the system performance by exploiting the channel's degrees of freedom in the elevation through the dynamic adaptation of the vertical antenna beam pattern. This necessitates the derivation and characterization of three-dimensional (3D) channels. Over the years, channel models have evolved to address the challenges of wireless communication technologies. In parallel to theoretical studies on channel modeling, many standardized channel models like COST-based models, 3GPP SCM, WINNER, ITU have emerged that act as references for industries and telecommunication companies to assess system-level and link-level performances of advanced signal processing techniques over real-like channels. Given the existing channels are only two dimensional (2D) in nature; a large effort in channel modeling is needed to study the impact of the channel component in the elevation direction. The first part of this work sheds light on the current 3GPP activity around 3D channel modeling and beamforming, an aspect that to our knowledge has not been extensively covered by a research publication. The standardized MIMO channel model is presented, that incorporates both the propagation effects of the environment and the radio effects of the antennas. In order to facilitate future studies on the use of 3D beamforming, the main features of the proposed 3D channel model are discussed. A brief overview of the future 3GPP 3D channel model being outlined for the next generation of wireless networks is also provided. In the subsequent part of this work, we present an information-theoretic channel model for MIMO systems that supports the elevation dimension. The model is based on the principle of maximum entropy, which enables us to determine the distribution of the channel matrix consistent with the prior information on the angles of departure and angles of arrival of the propagation paths. Based on this model, an analytical expression for the cumulative density function (CDF) of the mutual information (MI) for systems with a single receive and finite number of transmit antennas in the general signal-to-interference-plus-noise-ratio (SINR) regime is provided. The result is extended to systems with multiple receive antennas in the low SINR regime. A Gaussian approximation to the asymptotic behavior of the MI distribution is derived for the large number of transmit antennas and paths regime. Simulation results study the performance gains realizable through meticulous selection of the transmit antenna down tilt angles, confirming the potential of elevation beamforming to enhance system performance. The results validate the proposed analytical expressions and elucidate the dependence of system performance on azimuth and elevation angular spreads and antenna patterns. We believe that the derived expressions will help evaluate the performance of 3D 5G massive MIMO systems in the future.