Complex Lattice Reduction Algorithm for Low-Complexity Full-Diversity MIMO Detection

Recently, lattice-reduction-aided detectors have been proposed for multiinput multioutput (MIMO) systems to achieve performance with full diversity like the maximum likelihood receiver. However, these lattice-reduction-aided detectors are based on the traditional Lenstra-Lenstra-Lovasz (LLL) reducti...

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Bibliographic Details
Published in:IEEE transactions on signal processing Vol. 57; no. 7; pp. 2701 - 2710
Main Authors: Ying Hung Gan, Ying Hung Gan, Cong Ling, Cong Ling, Wai Ho Mow, Wai Ho Mow
Format: Journal Article
Language:English
Published: New York, NY IEEE 01.07.2009
Institute of Electrical and Electronics Engineers
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Algorithm design and analysis
Algorithms
Analytical models
Applied sciences
Channels
Coding, codes
Complex-valued algorithm
Complexity
complexity reduction
Computer simulation
Detectors
Exact sciences and technology
Gallium nitride
Information, signal and communications theory
lattice reduction
Lattices
Mathematical analysis
Matrix decomposition
Maximum likelihood decoding
Maximum likelihood detection
MIMO
Miscellaneous
multiinput multioutput (MIMO)
Reduction
Signal and communications theory
Signal processing
Signal processing algorithms
Studies
Telecommunications and information theory
Performance evaluation
MIMO system
Maximum likelihood receiver
Bit error rate
lattice reduction
Decoding
Algorithm
Complex variable method
Upper bound
Simulation
Complex―valued algorithm
Algorithm complexity
multiinput multioutput (MIMO)
Signal processing
complexity reduction
ISSN:1053-587X, 1941-0476
Online Access:Get full text
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Summary:Recently, lattice-reduction-aided detectors have been proposed for multiinput multioutput (MIMO) systems to achieve performance with full diversity like the maximum likelihood receiver. However, these lattice-reduction-aided detectors are based on the traditional Lenstra-Lenstra-Lovasz (LLL) reduction algorithm that was originally introduced for reducing real lattice bases, in spite of the fact that the channel matrices are inherently complex-valued. In this paper, we introduce the complex LLL algorithm for direct application to reducing the basis of a complex lattice which is naturally defined by a complex-valued channel matrix. We derive an upper bound on proximity factors, which not only show the full diversity of complex LLL reduction-aided detectors, but also characterize the performance gap relative to the lattice decoder. Our analysis reveals that the complex LLL algorithm can reduce the complexity by nearly 50% compared to the traditional LLL algorithm, and this is confirmed by simulation. Interestingly, our simulation results suggest that the complex LLL algorithm has practically the same bit-error-rate performance as the traditional LLL algorithm, in spite of its lower complexity.
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ISSN:1053-587X
1941-0476
DOI:10.1109/TSP.2009.2016267