55 citations · 109 across the 18 of their papers we have counts for
10 papers · 1 filter
SafeSlice: Enabling SLA-Compliant O-RAN Slicing via Safe Deep Reinforcement Learning
Ahmad M. Nagib, Hatem Abou-Zeid, Hossam S. Hassanein
Deep reinforcement learning (DRL)-based slicing policies have shown significant success in simulated environments but face challenges in physical systems such as open radio access…
Safe and Accelerated Deep Reinforcement Learning-based O-RAN Slicing: A Hybrid Transfer Learning Approach
Ahmad M. Nagib, Hatem Abou-Zeid, Hossam S. Hassanein
The open radio access network (O-RAN) architecture supports intelligent network control algorithms as one of its core capabilities. Data-driven applications incorporate such algori…
How Does Forecasting Affect the Convergence of DRL Techniques in O-RAN Slicing?
Ahmad M. Nagib, Hatem Abou-Zeid, Hossam S. Hassanein
The success of immersive applications such as virtual reality (VR) gaming and metaverse services depends on low latency and reliable connectivity. To provide seamless user experien…
Using Early Exits for Fast Inference in Automatic Modulation Classification
Elsayed Mohammed, Omar Mashaal, Hatem Abou-Zeid
Automatic modulation classification (AMC) plays a critical role in wireless communications by autonomously classifying signals transmitted over the radio spectrum. Deep learning (D…
Accelerating and Compressing Deep Neural Networks for Massive MIMO CSI Feedback
Omar Erak, Hatem Abou-Zeid
The recent advances in machine learning and deep neural networks have made them attractive candidates for wireless communications functions such as channel estimation, decoding, an…
Toward Safe and Accelerated Deep Reinforcement Learning for Next-Generation Wireless Networks
Ahmad M. Nagib, Hatem Abou-zeid, Hossam S. Hassanein
Deep reinforcement learning (DRL) algorithms have recently gained wide attention in the wireless networks domain. They are considered promising approaches for solving dynamic radio…
Structure-aware reinforcement learning for node-overload protection in mobile edge computing
Anirudha Jitani, Aditya Mahajan, Zhongwen Zhu +3
Mobile Edge Computing (MEC) refers to the concept of placing computational capability and applications at the edge of the network, providing benefits such as reduced latency in han…
A Lookback Scheduling Framework for Long-Term Quality-of-Service Over Multiple Cells
Hatem Abou-zeid, Hossam S. Hassanein, Stefan Valentin +1
In current cellular networks, schedulers allocate wireless channel resources to users based on instantaneous channel gains and short-term moving averages of user rates and queue le…
Energy-Efficient Adaptive Video Transmission: Exploiting Rate Predictions in Wireless Networks
Hatem Abou-zeid, Hossam S. Hassanein, Stefan Valentin
The unprecedented growth of mobile video traffic is adding significant pressure to the energy drain at both the network and the end user. Energy efficient video transmission techni…
Predictive Green Wireless Access: Exploiting Mobility and Application Information
Hatem Abou-zeid, Hossam S. Hassanein
The ever increasing mobile data traffic and dense deployment of wireless networks have made energy efficient radio access imperative. As networks are designed to satisfy peak user…