105 citations · 126 across the 29 of their papers we have counts for
29 papers
WiSDoM: Wireless Sparse Decision Transformer with Mixture-of-Experts for Multi-Task Mobile Network Optimization
Fatih Temiz, Shavbo Salehi, Melike Erol-Kantarci
Emerging 6G wireless networks are expected to operate across diverse deployment scenarios, where variations in network topology, user mobility, traffic demand, and radio conditions…
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…
Multi-Agent Reinforcement Learning for Online Traffic Scheduling in Time-Sensitive Application
Marcos Carvalho, Fatih Temiz, Shavbo Salehi +2
Time-sensitive networking (TSN) is increasingly integrated into mobile edge computing (MEC) to support applications with stringent latency requirements, such as extended reality (X…
Multi-Agent Transformer for Queue-Level XR Traffic Scheduling in TSN Networks
Marcos Carvalho, Fatih Temiz, Shavbo Salehi +2
Time-Sensitive Networking (TSN) and Mobile Edge Computing (MEC) hold strong potential for enabling ultra-reliable low-latency communication for time-sensitive applications, such as…
FedCritic-MIMO: Communication-Efficient Serverless Federated Critic Learning for Massive-MIMO Resource Control in Open and Disaggregated 6G RANs
Amin Farajzadeh, Melike Erol-Kantarci
This paper proposes FedCritic-MIMO, a communication-efficient serverless federated multi-agent reinforcement learning framework for AI-native resource control across independently…
FedCritic: Serverless Federated Critic Learning-based Resource Allocation for Multi-Cell OFDMA in 6G
Amin Farajzadeh, Melike Erol-Kantarci
In sixth-generation (6G) ultra-dense networks, aggressive frequency reuse amplifies inter-cell interference (ICI), making multi-cell orthogonal frequency-division multiple access (…
Edge Learning via Federated Split Decision Transformers for Metaverse Resource Allocation
Fatih Temiz, Shavbo Salehi, Melike Erol-Kantarci
Mobile edge computing (MEC) based wireless metaverse services offer an untethered, immersive experience to users, where the superior quality of experience (QoE) needs to be achieve…
SkyNetPredictor: Network Performance Prediction in Avionic Communication using AI
Hind Mukhtar, Raymond Schaub, Melike Erol-Kantarci
Satellite-based communication systems are integral to delivering high-speed data services in aviation, particularly for business aviation operations requiring global connectivity.…
LLM-Enabled Data Transmission in End-to-End Semantic Communication
Shavbo Salehi, Melike Erol-Kantarci, Dusit Niyato
Emerging services such as augmented reality (AR) and virtual reality (VR) have increased the volume of data transmitted in wireless communication systems, revealing the limitations…
Prioritized Value-Decomposition Network for Explainable AI-Enabled Network Slicing
Shavbo Salehi, Pedro Enrique Iturria-Rivera, Medhat Elsayed +4
Network slicing aims to enhance flexibility and efficiency in next-generation wireless networks by allocating the right resources to meet the diverse requirements of various applic…
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…
Joint Task Offloading and User Scheduling in 5G MEC under Jamming Attacks
Mohammadreza Amini, Burak Kantarci, Claude D'Amours +1
In this paper, we propose a novel joint task offloading and user scheduling (JTO-US) framework for 5G mobile edge computing (MEC) systems under security threats from jamming attack…
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…