TítuloDeep Learning Assisted Rate Adaptation in Spatial Modulation Links
Tipo de publicaciónConference Paper
Year of Publication2019
AutoresTato, A, Mosquera, C
Conference Name16th International Symposium on Wireless Communication Systems (ISWCS)
Conference LocationOulu (Finland)
Palabras claveDeep Learning, link adaptation, Machine Learning, Spatial Modulation
Resumen

The adaptation of Spatial Modulation based links to the channel conditions is challenged by the complicated dependence between performance (either error rate metrics or theoretically achievable rates) and the multiple antenna channel description. In this paper a coding rate selection mechanism is presented based on a carefully selected set of channel features and the proper training of a deep neural network, which all together can satisfy a given error rate bound.