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Spatial Modulation for Beyond 5G Communications: Capacity Calculation and Link Adaptation

AtlanTTic Research Center, Universidade de Vigo, 36310 Vigo, Spain
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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))
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.
Keywords: link adaptation; adaptive coding and modulation; spatial modulation; 5G; neural networks; machine learning; deep learning link adaptation; adaptive coding and modulation; spatial modulation; 5G; neural networks; machine learning; deep learning
MDPI and ACS Style

Tato, A.; Mosquera, C. Spatial Modulation for Beyond 5G Communications: Capacity Calculation and Link Adaptation. Proceedings 2019, 21, 26.

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