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Low-complexity detection for spatial modulation

  • The computational complexity of the optimal maximum likelihood (ML) detector for spatial modulation increases rapidly as more transmit antennas or larger modulation orders are employed. Hence, ML detection may be infeasible for higher bit rates. This work proposes an improved suboptimal detection algorithm based on the Gaussian approximation method. It is demonstrated that the new method is closely related to the previously published signal vector based detection and the modified maximum ratio combiner, but can improve the detection performance compared to these methods. Furthermore, the performance of different signal constellations with suboptimal detection is investigated. Simulation results indicate that the performance loss compared to ML detection depends heavily on the signal constellation, where the recently proposed Eisenstein integer constellations are beneficial compared to classical QAM or PSK constellations.

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Metadaten
Author:Jürgen FreudenbergerORCiDGND, Daniel Rohweder, Sergo ShavgulidzeORCiD
URL:https://ieeexplore.ieee.org/document/8661350
DOI:https://doi.org/10.30420/454862053
ISBN:978-3-8007-4862-4
Parent Title (English):SCC 2019; 12th International ITG Conference on Systems, Communications and Coding, February 11 - 14, 2019, Rostock, Germany
Publisher:VDE Verlag
Place of publication:Berlin ; Offenbach
Document Type:Conference Proceeding
Language:English
Year of Publication:2019
Release Date:2020/01/13
First Page:309
Last Page:313
Note:
Volltextzugriff für Hochschulangehörige via Datenbank IEEE Xplore möglich
Institutes:Institut für Systemdynamik - ISD
DDC functional group:000 Allgemeines, Informatik, Informationswissenschaft
Relevance:Keine peer reviewed Publikation (Wissenschaftlicher Artikel und Aufsatz, Proceeding, Artikel in Tagungsband)
Open Access?:Nein
Licence (English):License LogoLizenzbedingungen IEEE