Complex Korkine-Zolotareff Reduction Algorithm for Full-Diversity MIMO Detection

The Korkine-Zolotareff (KZ) reduced basis is considered as the best reduced basis for use in data decoding in multiple-input multiple-output (MIMO) communication systems. In this paper, we present an improved KZ algorithm for direct application in reducing a complex lattice basis. The enumeration al...

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Veröffentlicht in:IEEE communications letters Jg. 17; H. 2; S. 381 - 384
Hauptverfasser: Jiang, Hua, Du, Sidan
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York, NY IEEE 01.02.2013
Institute of Electrical and Electronics Engineers
Schlagworte:
Applied sciences
Bit error rate
Coding, codes
Decoding
Detectors
enumeration algorithm
Exact sciences and technology
full diversity
Information, signal and communications theory
Korkine-Zolotareff reduction
lattice reduction
Lattices
MIMO
multiple-input multiple-output (MIMO)
Signal and communications theory
Signal processing algorithms
Telecommunications and information theory
Vectors
Performance evaluation
MIMO system
Iterative method
lattice reduction
Decoding
multiple-input multiple-output (MIMO)
Algorithm
full diversity
Simulation
enumeration algorithm
Telecommunication system
Algorithm complexity
Korkine-Zolotareff reduction
ISSN:1089-7798
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Zusammenfassung:The Korkine-Zolotareff (KZ) reduced basis is considered as the best reduced basis for use in data decoding in multiple-input multiple-output (MIMO) communication systems. In this paper, we present an improved KZ algorithm for direct application in reducing a complex lattice basis. The enumeration algorithm, which is the dominant contributor to the main cost of the KZ algorithm, is also modified for a complex lattice. We reduce the number of iterations in the KZ algorithm to reduce complexity without degrading performance. In addition, we show that KZ-reduction-aided decoding is capable of achieving full diversity. Simulation results demonstrate the excellent performance and low complexity of the improved algorithm.
ISSN:1089-7798
DOI:10.1109/LCOMM.2013.010313.122418