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Feedback in multiple antenna wireless communication systems
Multiple-input multiple-output wireless systems promise significant capacity gain
and/or diversity gain over single antenna systems. If channel state information (CSI)
is available at both the transmitter and the receiver, the performance can be further
improved. In this thesis, first, we study binary index feedback problem in beamforming
systems when the feedback channel is not error free. Feedback errors lead to incorrect
beamforming vectors to be applied at the transmitter and thus degrade beamforming
performance. Index-assignment algorithms that minimize the impact of feedback errors
are proposed. Second, in the limited feedback beamforming scheme the receiver has to
determine the best codeword from the beamforming codebook. Exhaustive codeword
search for large-size codebooks becomes a burden when the receiver is a mobile device
with limited computational power. We propose an algorithm to drastically reduce codeword
selection complexity with negligible performance loss. Third, we compare angle
feedback scheme and transmit antenna shuffling feedback scheme for double space-time
transmit diversity systems. We show that the 1-bit angle feedback scheme does not
provide a better performance than the 1-bit antenna shuffling feedback scheme. Fourth,
we consider training power allocation for a closed-loop MIMO system in i.i.d. Rayleigh
flat-fading channels with power constraint. We derive the optimal solution and asymptotic
optimal solution of training power allocation for spatial power control and spatial
and fading power control. Lastly, we analyze the optimal diversity-multiplexing tradeoff
of multiple beamforming systems and compare it with the well known result for MIMO
channels with channel state information at the receiver (CSIR) only and with the optimal
diversity-multiplexing tradeoff of spatial multiplexing system with channel state
information at the transmitter (CSIT), but without coding over space and time
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