Opportunistic Beamforming is a promising scheme with potential usage in a variety of applications ranging from cellular audio/video communications to wireless mesh-networks. However, some aspects in this scheme are open to further improvements, such as effective quality of service (QoS) provisioning, and efficient handling of sparse/realistic networks. We focus on the downlink channel of a multi-rate time-division multiplexing MISO (multiple input single output) point-to-multi-point wireless communication system, and design a cross-layer scheme. We employ a two-stage opportunistic scheduler. The scheduler receives channel state information in the form of SNR (signal to noise ratio) measurements from each terminal, and schedules one terminal in each time-slot. At the first stage in a time-slot a terminal is chosen, and our gradient descent channel estimator finds an estimation of its channel vector. Then the beamformer produces a beamforming vector in an adjacent pilot channel, or in the first part of the time-slot in the data channel. Our beamforming is based on the estimation of the channel, as opposed to the random beamformer used in the opportunistic beamforming. Each terminal measures its perceived SNR even when the channel is assigned to another terminal, and sends this information back to the basestation subject to a feedback-reduction policy. The scheduler uses the new channel state information for its second stage and assigns a terminal for the succeeding time-slot. The channel estimation procedure uses the reported SNRs for each terminal, which is a significantly lower feedback rate than the amount required for coherent beamforming. Our approach efficiently handles sparse/realistic networks, and also provides a better QoS than the opportunistic beamforming scheme. / Thesis (Master, Electrical & Computer Engineering) -- Queen's University, 2007-06-30 07:00:20.468