  Recent successes and advances in Deep Neural Networks (DNN) in machine vision
and Natural Language Processing (NLP) have motivated their use in traditional
signal processing and communications systems. In this paper, we present results
of such applications to the problem of automatic modulation recognition.
Variations in wireless communication channels are represented by statistical
channel models and their parameterization will increase with the advent of 5G.
In this paper, we report effect of simple two path channel model on our naive
deep neural network based implementation. We also report impact of adversarial
perturbation to the input signal.
