105 citations · 126 across the 29 of their papers we have counts for
6 papers · 1 filter
Agentic Quantum Deep Reinforcement Learning for RAN Slicing
Tingnan Bao, Medhat Elsayed, Pedro Enrique Iturria-Rivera +3
Radio access network (RAN) slicing enables ultra-reliable low-latency communications (URLLC) and enhanced mobile broadband (eMBB) services to share radio resources, but their requi…
Sum Rate Enhancement using Machine Learning for Semi-Self Sensing Hybrid RIS-Enabled ISAC in THz Bands
Sara Farrag Mobarak, Tingnan Bao, Melike Erol-Kantarci
This paper proposes a novel semi-self sensing hybrid reconfigurable intelligent surface (SS-HRIS) in terahertz (THz) bands, where the RIS is equipped with reflecting elements divid…
Heuristic Deep Reinforcement Learning for Phase Shift Optimization in RIS-assisted Secure Satellite Communication Systems with RSMA
Tingnan Bao, Melike Erol-Kantarci
This paper presents a novel heuristic deep reinforcement learning (HDRL) framework designed to optimize reconfigurable intelligent surface (RIS) phase shifts in secure satellite co…
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…
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…
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…