Deep Neural Networks based Modrec: Some Results with Inter-Symbol Interference and Adversarial Examples
Machine Learning
2018-11-16 v1 Signal Processing
Machine Learning
Abstract
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.
Cite
@article{arxiv.1811.06103,
title = {Deep Neural Networks based Modrec: Some Results with Inter-Symbol Interference and Adversarial Examples},
author = {S. Asim Ahmed and Subhashish Chakravarty and Michael Newhouse},
journal= {arXiv preprint arXiv:1811.06103},
year = {2018}
}
Comments
4 pages, 13 figures