4 citations · 6 across the 9 of their papers we have counts for
8 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…
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,…
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…
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…
Hierarchical Reinforcement Learning Based Traffic Steering in Multi-RAT 5G Deployments
Md Arafat Habib, Hao Zhou, Pedro Enrique Iturria-Rivera +5
In 5G non-standalone mode, an intelligent traffic steering mechanism can vastly aid in ensuring smooth user experience by selecting the best radio access technology (RAT) from a mu…
Hierarchical Deep Q-Learning Based Handover in Wireless Networks with Dual Connectivity
Pedro Enrique Iturria Rivera, Medhat Elsayed, Majid Bavand +3
5G New Radio proposes the usage of frequencies above 10 GHz to speed up LTE's existent maximum data rates. However, the effective size of 5G antennas and consequently its repercuss…