6 citations · 8 across the 11 of their papers we have counts for
13 papers · 1 filter
Deadline-Aware Multi-Agent Reinforcement Learning for TSN-Based Vehicular Edge Networks
Bernardo A. C. Pereira, Marcos Carvalho, Fatih Temiz +5
Vehicular edge computing (VEC) enables latency-sensitive applications by bringing computing and networking resources closer to vehicles. However, existing approaches often overlook…
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…
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…
Generalizable Multi-Task Learning for Wireless Networks Using Prompt Decision Transformers
Fatih Temiz, Shavbo Salehi, Melike Erol-Kantarci
Future wireless networks demand rapid adaptation to highly heterogeneous environments and dynamic task configurations, necessitating a shift from conventional rule-based and optimi…
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…
GenAI-enabled Residual Motion Estimation for Energy-Efficient Semantic Video Communication
Shavbo Salehi, Pedro Enrique Iturria-Rivera, Medhat Elsayed +3
Semantic communication addresses the limitations of the Shannon paradigm by focusing on transmitting meaning rather than exact representations, thereby reducing unnecessary resourc…
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…
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…
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…
An Optimal Multi-UAV Deployment Model for UAV-assisted Smart Farming
Shavbo Salehi, Jahan Hassan, Ayub Bokani
Next-generation wireless networks will deploy UAVs dynamically as aerial base stations (UAV-BSs) to boost the wireless network coverage in the out of reach areas. To provide an eff…
Energy and Service-priority aware Trajectory Design for UAV-BSs using Double Q-Learning
Sayed Amir Hoseini, Ayub Bokani, Jahan Hassan +2
Next-generation mobile networks have proposed the integration of Unmanned Aerial Vehicles (UAVs) as aerial base stations (UAV-BS) to serve ground nodes. Despite having advantages o…