The objective of the dissertation research is to understand the complex
interaction between the algorithm and hardware aspects of symbol
detection that is enhanced by lattice reduction (LR) preprocessing for
wireless MIMO communication systems. The motivation for this work stems
from the need to improve the bit-error-rate performance of conventional,
low-complexity detectors while simultaneously exhibiting considerably
reduced complexity when compared to the optimal method, maximum
likelihood detection. Specifically, we first develop an understanding of
the complex Lenstra-Lenstra-Lovász (CLLL) LR algorithm from a hardware
perspective. This understanding leads to both algorithm modifications
that reduce the required complexity and hardware architectures that are
specifically optimized for the CLLL algorithm. Finally, we integrate
this knowledge with an understanding of LR-aided MIMO symbol detection
in a highly-correlated wireless environment, resulting in a joint
LR/symbol detection algorithm that maps seamlessly to hardware. Hence,
this dissertation forms the foundation for the adoption of lattice
reduction algorithms in practical, high-throughput wireless MIMO
communications systems.
| Identifer | oai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/39591 |
| Date | 04 April 2011 |
| Creators | Gestner, Brian Joseph |
| Publisher | Georgia Institute of Technology |
| Source Sets | Georgia Tech Electronic Thesis and Dissertation Archive |
| Detected Language | English |
| Type | Dissertation |
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