The future wireless networks have an emphasis on a remarkable increase in data rate with a huge number of users. This matter will cause the increasing demand for base stations which leads to an increase in the power consumption in the wireless networks. In this research, we considered a multi-user MIMO network. The goal is to design pre-coder matrices at the transmitters to increase the sum-rate. The proposed method is a semi-distributed method that needs low information feedback. We also investigated the performance and computational complexity of the proposed method. The simulation results reveal the decreasing computational complexity compared with the newest method which provides the opportunity to use in a large number of antennas. In the sequel, we investigate the effects of channel estimation error on the performance of the proposed method. In the second part of this thesis, we consider the energy efficiency maximization problem in MIMO interference channels. We design the transmit beamforming matrices based on three approaches. In the first approach, each user tries to maximize their energy efficiency, resulting in what we call the selfish method. The second approach aims to maximize the weighted sum-energy efficiency; we refer to it as the unselfish method. Also, we consider fairness with the minimum-energy efficiency maximization problem; an approach that results in what we call the worst-case method. The third part investigates the energy-efficient pre-coder design in multi-user MIMO systems which is also robust to the imperfect channel state information at the transmitters. We investigate the problem in two conventional cases. The first case considers the statistical characterization for the channel estimation error with a semi-closed-form solution. Then, we turn our attention to the case which considers only the uncertainty region for the channel estimation error. Key Words Pre-coder, Energy Efficiency, Spectral Efficiency, Interference Channel
