Título | Neural Network Aided Computation of Generalized Spatial Modulation Capacity |
Tipo de publicación | Conference Paper |
Year of Publication | 2019 |
Autores | Tato, A, Mosquera, C, Henarejos, P, Pérez-Neira, A |
Conference Name | 27th European Signal Processing Conference (EUSIPCO) |
Conference Location | A Coruña (Spain) |
Palabras clave | Generalized Spatial Modulation, Index Modulations, Machine Learning, Multilayer Feedforward Neural Network, Polarized Modulation |
Resumen | Generalized Spatial Modulation (GSM) is being considered for future high-capacity and energy efficient terrestrial networks. A variant such as Polarized Modulation (PMod) has also a role in Dual Polarization Mobile Satellite Systems. The implementation of adaptive GSM systems requires fast methods to evaluate the channel dependent GSM capacity, which amounts to solve multi-dimensional integrals without closed-form solutions. For this purpose, we propose the use of a Multilayer Feedforward Neural Network and an associated feature selection algorithm. The resulting method is highly accurate and with much lower complexity than alternative numerical methods. |