Spatial Modulation for Beyond 5G Communications: Capacity Calculation and Link Adaptation †
AtlanTTic Research Center, Universidade de Vigo, 36310 Vigo, Spain
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Author to whom correspondence should be addressed.
†
Presented at the 2nd XoveTIC Conference, A Coruña, Spain, 5–6 September 2019.
Proceedings 2019, 21(1), 26; https://doi.org/10.3390/proceedings2019021026
Published: 31 July 2019
(This article belongs to the Proceedings of The 2nd XoveTIC Conference (XoveTIC 2019))
Abstract
Spatial Modulation (SM) is a candidate modulation scheme for beyond 5G communications systems due to its reduced hardware complexity and good trade-off between energy and spectral efficiency. This paper proposes two Machine Learning based solutions for easing the implementation of adaptive SM systems. On the one hand, a shallow neural network is shown to be an accurate and simple method for obtaining the capacity of SM. On the other hand, a deep neural network is proposed to select the coding rate in practical adaptive SM systems.
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MDPI and ACS Style
Tato, A.; Mosquera, C. Spatial Modulation for Beyond 5G Communications: Capacity Calculation and Link Adaptation. Proceedings 2019, 21, 26. https://doi.org/10.3390/proceedings2019021026
AMA Style
Tato A, Mosquera C. Spatial Modulation for Beyond 5G Communications: Capacity Calculation and Link Adaptation. Proceedings. 2019; 21(1):26. https://doi.org/10.3390/proceedings2019021026
Chicago/Turabian StyleTato, Anxo, and Carlos Mosquera. 2019. "Spatial Modulation for Beyond 5G Communications: Capacity Calculation and Link Adaptation" Proceedings 21, no. 1: 26. https://doi.org/10.3390/proceedings2019021026
