  In this paper, deep neural network (DNN) is integrated with spatial
modulation-orthogonal frequency division multiplexing (SM-OFDM) technique for
end-to-end data detection over Rayleigh fading channel. This proposed system
directly demodulates the received symbols, leaving the channel estimation done
only implicitly. Furthermore, an ensemble network is also proposed for this
system. Simulation results show that the proposed DNN detection scheme has a
significant advantage over classical methods when the pilot overhead and cyclic
prefix (CP) are reduced, owing to its ability to learn and adjust to
complicated channel conditions. Finally, the ensemble network is shown to
improve the generalization of the proposed scheme, while also showing a slight
improvement in its performance.
