Exploring the Artificial Intelligence for Wireless Communication Applications

Abstract depiction of high-speed wireless services

Department of Electrical and Computer Engineering

Location: Burchard 714

Speaker: Huaxia Wang, Rowan University


With the advancement of Deep Learning (DL) and Artificial Intelligence (AI), extensive research is being carried out in various application domains such as image classification, speech recognition, and wireless communications. In the first part of the presentation, we propose a novel and defensive mechanism based on a Generative Adversarial Network (GAN) framework to achieve robust end-to-end learning of a communications system. We utilize a generative network to model a powerful adversary and enable the end-to-end communications system to combat the generative attack network via a minimax game. In the second part, we propose a novel algorithm for allocating distributed spectrum and power resources in vehicular networks, including both vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication links. The proposed algorithm utilizes imitation learning and Graph Neural Network (GNN) to train distributed policies that adhere to the local structure of the vehicular system while imitating a centralized policy.


Head shot of Huaxia Wang wearing glasses, smiling

Huaxia Wang is an assistant professor in the Department of Electrical & Computer Engineering at Rowan University. He received his Bachelor of Engineering (B.Eng) degree in Information Engineering from Southeast University, Nanjing, China, in 2012, and a Ph.D. degree in Electrical Engineering from the Stevens Institute of Technology, Hoboken, NJ, in 2018. Prior to joining Rowan in the fall 2023, he was an assistant professor at Oklahoma State University from 2020 to 2023, a research engineer at Futurewei Technology from 2018 to 2019, and a research intern at Nokia Bell Labs in 2016. His research focuses on AI in wireless communications, adversarial learning, deep reinforcement learning, and robotics.