| In Multiple-Input Multiple-Output (MIMO) broadcast channels, the multi-antenna basestation transmits information to multiple non-cooperative mobile users simultaneously. Among various transmission schemes, zero-forcing beamforming (ZFBF) and random unitary beamforming (RUB) are of particular interest due to their low implementation complexity and ability to explore the multiplexing gain provided by multiple transmit antennas.;In addition to beamforming techniques, we study the symbol error rate (SER) performance of MIMO broadcast channels with vector perturbation (VP) precoding and quantized channel feedback. Based on the established equivalent relations in terms of minimum mean square error (MMSE) and SER between quantized and perfect channel feedback cases, we investigate the tradeoff between feedback load and achievable diversity gain.;To investigate the effects of multiuser diversity on sum-rate performance, previous studies of beamforming schemes in multiuser MIMO systems usually employ asymptotical analysis. In this work, while assuming channel gain follows Rayleigh flat fading, we study the sum-rate performance of ZFBF and RUB through exact mathematic analysis. For this purpose, we derive the statistics of selected users's effective channel gain, which enable us to calculate the sum rate accurately and efficiently. With derived sum-rate expressions, we evaluate and compare the sum-rate performance of MIMO broadcast channels with RUB and dual-transmit-antenna ZFBF. In addition, we apply this analytical method to study strategies that mitigate multiuser interference for RUB-based multiuser MIMO systems. The strategies we consider in the thesis include (1) Reducing the number of served users at a time. We present a new user scheduling scheme, which imposes a threshold on user's SINR for feedback load reduction and only activates those beams that are requested by feedback users. (2) Exploiting receive diversity. When receivers use more than one antennas, we evaluate the sum-rate performance gain offered by selection combining (SC) and optimum combining (OC) schemes, respectively. |
