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

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Název: Spatial Modulation for Beyond 5G Communications: Capacity Calculation and Link Adaptation
Autoři: Anxo Tato, Carlos Mosquera
Zdroj: Proceedings, Vol 21, Iss 1, p 26 (2019)
Informace o vydavateli: MDPI AG
Rok vydání: 2019
Sbírka: Directory of Open Access Journals: DOAJ Articles
Témata: link adaptation, adaptive coding and modulation, spatial modulation, 5G, neural networks, machine learning, deep learning, General Works
Popis: 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.
Druh dokumentu: article in journal/newspaper
Jazyk: English
Relation: https://www.mdpi.com/2504-3900/21/1/26; https://doaj.org/toc/2504-3900; https://doaj.org/article/74d98cbdc46e47908846549dc9a2b0cf
DOI: 10.3390/proceedings2019021026
Dostupnost: https://doi.org/10.3390/proceedings2019021026
https://doaj.org/article/74d98cbdc46e47908846549dc9a2b0cf
Přístupové číslo: edsbas.12AE5292
Databáze: BASE
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  – Url: https://doi.org/10.3390/proceedings2019021026#
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  Data: Spatial Modulation for Beyond 5G Communications: Capacity Calculation and Link Adaptation
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  Data: <searchLink fieldCode="AR" term="%22Anxo+Tato%22">Anxo Tato</searchLink><br /><searchLink fieldCode="AR" term="%22Carlos+Mosquera%22">Carlos Mosquera</searchLink>
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  Data: Proceedings, Vol 21, Iss 1, p 26 (2019)
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  Data: 2019
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  Data: 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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      – SubjectFull: link adaptation
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      – SubjectFull: spatial modulation
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