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MIMO 經典論文
This thesis report focuses on wireless communication systems with multiple transmit and multiple
receive antennas. At first, we study the performance of such systems assuming a spatial
multiplexing scheme at the transmitter and an ML detection at the receiver. We derive an
accurate approximation for the conditional error probability on a quasi static channel. This
approximation is computed when distinct modulations are applied on the transmit antennas
and for any MIMO channel configuration.
Then, we outline some adaptive techniques for MIMO systems: adaptive modulation and antenna
selection. The first one adjusts the modulations on transmit antennas according to the
channel conditions in order to maximize the spectral efficiency while satisfying a constraint on
error probability. The second technique selects the set of active antennas to optimize the chosen
selection criterion (e.g. maximize the capacity, etc) providing a channel estimation. Both adaptive
techniques need a relevant matric to evaluate the MIMO system performance. We propose
a new adaptive modulation scheme and antenna selection algorithm where the derived error
probability approximation is used as a selection metric.
Finally, we consider the quantization of MIMO channels. This quantization, in our terminology
classification, allows the partitioning of MIMO channels set into different classes, where each
class is identified by a representative. This method could be used for adaptive techniques to
find the best adjustable parameters. We describe our MIMO classification algorithm and we
illustrate its application for closed-loop MIMO systems, e.g beamforming. |
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eetop公众号
创芯大讲堂
创芯人才网
发表于 2008-3-10 20:31:38
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