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Extended 4-point approximation of the optimal QAM modulation detector

 
: Chen, Yun; Husmann, Christopher; Saad, Ahmad; Heidrich, Mike

:

Institute of Electrical and Electronics Engineers -IEEE-; IEEE Communications Society:
IEEE 25th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications, PIMRC 2014. Vol.2 : Washington, DC, USA, 2 - 5 September 2014
Piscataway, NJ: IEEE, 2014
ISBN: 978-1-4799-4912-0
ISBN: 978-1-4799-4911-3
pp.743-747
International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC) <25, 2014, Washington/DC>
English
Conference Paper
Fraunhofer ESK ()
approximation theory; computational complexity; maximum likelihood estimation; quadrature amplitude modulation; QAM; maximum likelihood; ML; modulation detector; QAM modulation detection; computational efficient approximation; Smartgrid Communication; Wireless Networks

Abstract
Maximum likelihood (ML) based modulation detector is optimal in the sense that the detection error probability is minimized if no prior probability of candidate modulations is available at the detector. However, the high computational complexity of the ML-based detector strongly limits its practical implementation. This contribution deals with a computational efficient approximation of the ML-based method, which extends the existing 4-point approximation by utilizing the special arrangement of constellation points of square-formed quadrature amplitude modulation (QAM) schemes. Simulation results show that the extended 4-point approximation based detector is able to provide nearly optimal performance.

: http://publica.fraunhofer.de/documents/N-360501.html