105 citations · 126 across the 29 of their papers we have counts for
14 papers · 1 filter
Explainable Multi-Agent Reinforcement Learning for Extended Reality Codec Adaptation
Pedro Enrique Iturria-Rivera, Raimundas Gaigalas, Medhat Elsayed +3
Extended Reality (XR) services are set to transform applications over 5th and 6th generation wireless networks, delivering immersive experiences. Concurrently, Artificial Intellige…
The impact of mobility, beam sweeping and smart jammers on security vulnerabilities of 5G cells
Ghazal Asemian, Michel Kulhandjian, Mohammadreza Amini +3
The vulnerability of 5G networks to jamming attacks has emerged as a significant concern. This paper contributes in two primary aspects. Firstly, it investigates the effect of a mu…
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…
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…
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…
Sustainable Task Offloading in Secure UAV-assisted Smart Farm Networks: A Multi-Agent DRL with Action Mask Approach
Tingnan Bao, Aisha Syed, William Sean Kennedy +1
The integration of unmanned aerial vehicles (UAVs) with mobile edge computing (MEC) and Internet of Things (IoT) technology in smart farms is pivotal for efficient resource managem…
LLM-Based Intent Processing and Network Optimization Using Attention-Based Hierarchical Reinforcement Learning
Md Arafat Habib, Pedro Enrique Iturria Rivera, Yigit Ozcan +4
Intent-based network automation is a promising tool to enable easier network management however certain challenges need to be effectively addressed. These are: 1) processing intent…
Extended Reality (XR) Codec Adaptation in 5G using Multi-Agent Reinforcement Learning with Attention Action Selection
Pedro Enrique Iturria-Rivera, Raimundas Gaigalas, Medhat Elsayed +3
Extended Reality (XR) services will revolutionize applications over 5th and 6th generation wireless networks by providing seamless virtual and augmented reality experiences. These…
Large Language Models in Wireless Application Design: In-Context Learning-enhanced Automatic Network Intrusion Detection
Han Zhang, Akram Bin Sediq, Ali Afana +1
Large language models (LLMs), especially generative pre-trained transformers (GPTs), have recently demonstrated outstanding ability in information comprehension and problem-solving…
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…
DT-DDNN: A Physical Layer Security Attack Detector in 5G RF Domain for CAVs
Ghazal Asemian, Mohammadreza Amini, Burak Kantarci +1
The Synchronization Signal Block (SSB) is a fundamental component of the 5G New Radio (NR) air interface, crucial for the initial access procedure of Connected and Automated Vehicl…
Bypassing a Reactive Jammer via NOMA-Based Transmissions in Critical Missions
Mohammadreza Amini, Ghazal Asemian, Michel Kulhandjian +3
Wireless networks can be vulnerable to radio jamming attacks. The quality of service under a jamming attack is not guaranteed and the service requirements such as reliability, late…
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…
Adversarial Machine Learning-Enabled Anonymization of OpenWiFi Data
Samhita Kuili, Kareem Dabbour, Irtiza Hasan +4
Data privacy and protection through anonymization is a critical issue for network operators or data owners before it is forwarded for other possible use of data. With the adoption…