Performance Evaluation of Adaptive Arrays for MIMO Smart Antenna Systems
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Date
2011-08
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Addis Ababa University
Abstract
The demand for wireless systems has been growing rapidly over the recent years due to
improved reliability, high data rates, seamless connectivity and low deployment costs. MIMO
systems are the most efficient leading innovation of wireless systems for maximum capacity
and improved quality and coverage. This theory has been around for a long while but the
complexity involved and the signal processing required has been a major drawback to its widespread
use. However, recent improvements in Digital Signal Processing (DSP) technology has
made it possible to now construct such transmission systems.
In this thesis we study different adaptive blind and nonblind algorithms for MIMO systems
such as LMS, CMA, SMI, and combined algorithms, LMS-CMA, and SMI-CMA. Moreover,
we compare these adaptive array algorithms with other known class of MIMO linear receiver
(channel estimation) techniques like Zeroforcing (ZF) and minimum mean square error
(MMSE) methods. In addition to this, we have discussed Capacity of MIMO systems and
different MIMO transmission techniques such as spatial diversity (SD), Spatial
multiplexing(SM).
The results of performance evaluation for Adaptive array MIMO receivers revealed that LMS
has better BER performance than SMI, SMI-CMA, and ZF and the same performance with
MMSE with no need of CSI. LMS algorithm has slow convergence but low complexity
compared to MMSE algorithm that has fast convergence with very high complexity. Moreover,
the number of training signals can minimized by 62.5% at the cost of 2-4dB SNR using
nonblind algorithm( LMS) combined with blind algorithm( CMA).
Keywords: Adaptive arrays, MIMO systems, MIMO receivers, blind algorithms, nonblind
algorithms, LMS
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Keywords
Adaptive arrays, MIMO systems, MIMO receivers, Blind algorithms, Nonblind algorithms, Lml