no code implementations • 3 Feb 2024 • Ahmed P. Mohamed, Byunghyun Lee, Yaguang Zhang, Max Hollingsworth, C. Robert Anderson, James V. Krogmeier, David J. Love
To alleviate these challenges, this paper introduces a novel simulation-enhanced data augmentation method for ML pathloss prediction.
no code implementations • 7 Jan 2024 • Abu Shafin Mohammad Mahdee Jameel, Ahmed P. Mohamed, Jinho Yi, Aly El Gamal, Akshay Malhotra
In this paper, we investigate the effects of an adversarial attack on an AMC system that employs deep learning models both for AMC and for subsampling.
1 code implementation • 3 Apr 2021 • Ahmed P. Mohamed, Abu Shafin Mohammad Mahdee Jameel, Aly El Gamal
In this paper, we propose a framework for predicting frame errors in the collaborative spectrally congested wireless environments of the DARPA Spectrum Collaboration Challenge (SC2) via a recently collected dataset.
1 code implementation • 22 Mar 2020 • Abu Shafin Mohammad Mahdee Jameel, Ahmed P. Mohamed, Xiwen Zhang, Aly El Gamal
We demonstrate a first example for employing deep learning in predicting frame errors for a Collaborative Intelligent Radio Network (CIRN) using a dataset collected during participation in the final scrimmages of the DARPA SC2 challenge.