activity
20162026
most citedAI-enabled Future Wireless Networks: Challenges, Opportunities and Open Issues

157 citations · 221 across the 31 of their papers we have counts for

collaborators
Showing 2024 · cs.NIShow all

8 papers · 2 filters

cs.NI2024

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…

cs.NI2024

Cooperation and Personalization on a Seesaw: Choice-based FL for Safe Cooperation in Wireless Networks

Han Zhang, Medhat Elsayed, Majid Bavand +3

Federated learning (FL) is an innovative distributed artificial intelligence (AI) technique. It has been used for interdisciplinary studies in different fields such as healthcare,…

cs.NI2024★ 6 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.NI2024

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…