A low feedback robust opportunistic scheduler and beamformer for MISO wireless systems
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Authors
Honarvar, Ali
Date
2007-07-06T13:35:38Z
Type
thesis
Language
eng
Keyword
opportunistic beamforming , opportunistic scheduling
Alternative Title
Abstract
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.
Description
Thesis (Master, Electrical & Computer Engineering) -- Queen's University, 2007-06-30 07:00:20.468
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