most citedSmart Jamming Attack and Mitigation on Deep Transfer Reinforcement Learning Enabled Resource Allocation for Network Slicing

6 citations · 8 across the 10 of their papers we have counts for

collaborators

10 papers

cs.NI20246 cited

Smart Jamming Attack and Mitigation on Deep Transfer Reinforcement Learning Enabled Resource Allocation for Network Slicing

Shavbo Salehi, Hao Zhou, Medhat Elsayed +4

Network slicing is a pivotal paradigm in wireless networks enabling customized services to users and applications. Yet, intelligent jamming attacks threaten the performance of netw…

cs.NI2024

Machine Learning-enabled Traffic Steering in O-RAN: A Case Study on Hierarchical Learning Approach

Md Arafat Habib, Hao Zhou, Pedro Enrique Iturria-Rivera +5

Traffic Steering is a crucial technology for wireless networks, and multiple efforts have been put into developing efficient Machine Learning (ML)-enabled traffic steering schemes…

cs.NI2024

Self-Play Ensemble Q-learning enabled Resource Allocation for Network Slicing

Shavbo Salehi, Pedro Enrique Iturria-Rivera, Medhat Elsayed +4

In 5G networks, network slicing has emerged as a pivotal paradigm to address diverse user demands and service requirements. To meet the requirements, reinforcement learning (RL) al…

cs.NI20241 cited

Transformer-Based Wireless Traffic Prediction and Network Optimization in O-RAN

Md Arafat Habib, Pedro Enrique Iturria-Rivera, Yigit Ozcan +4

This paper introduces an innovative method for predicting wireless network traffic in concise temporal intervals for Open Radio Access Networks (O-RAN) using a transformer architec…

eess.SP2024

Federated Learning with Dual Attention for Robust Modulation Classification under Attacks

Han Zhang, Medhat Elsayed, Majid Bavand +3

Federated learning (FL) allows distributed participants to train machine learning models in a decentralized manner. It can be used for radio signal classification with multiple rec…

eess.SP2023

Beam Selection for Energy-Efficient mmWave Network Using Advantage Actor Critic Learning

Ycaro Dantas, Pedro Enrique Iturria-Rivera, Hao Zhou +4

The growing adoption of mmWave frequency bands to realize the full potential of 5G, turns beamforming into a key enabler for current and next-generation wireless technologies. Many…