Ahmed Mostafa Abdelhaleem Abdelkhalek
Faculty of Engieering Helwan University · Professor of Wireless communication at Faculty of Engieering Helwan University
Research Interests
Advanced network and data link layer protocols of both wired and wireless networks. Radio Access Networks for legacy and beyond 5G/6G systems, Cognitive radio networking, 3D networks, Software Defined Network, Internet of Things, Artificial Intelligent Based W...
Biography
AHMED M. ABD EL-HALEEM (Member, IEEE) received the B.Sc., M.Sc., and Ph.D. degrees in electronics and communications engineering from Helwan University, Cairo, Egypt, in 2001, 2006, and 2012, respectively. He is currently an Associate Professor with the Electronics and Communications Engineering Department, Faculty of Engineering, Helwan University. He is a member of a research team that awards several applied research projects funded by national and international funding agencies in the field of wireless communication, the IoT and its applications, and smart education systems. His current research interests include mobile/vehicular ad-hoc communication networks, 5G and 6G radio access networks, cognitive radio networking, device-to-device communication, the Internet of Things (IoT), reconfigurable intelligent surface (RIS), and AI application in wireless communication. This includes mobility management techniques and routing schemes for mobile ad-hoc networks (MANET).
Education
Bachelor of Engineering in Communication and Electronic Engineering - Helwan University – Cairo, Egypt. Date: 05/2001. Degree: Excellent with honors, the first. Master's Degree in Communication Engineering - Helwan University – Cairo, Egypt. Date: 11/2006. Doctoral Degree in Communication Engineering - Helwan University – Cairo, Egypt. Date: 01/2012.
Recent Scopus Publications
- Deep reinforcement learning for resource allocation and scalable numerology in NR-U enabled multi-RAT HetNets
- DRL-Driven Edge-Aware Utility Optimization for Multi-Slice 6G Networks
- Deep learning optimization of STAR-RIS for enhanced data rate and energy efficiency in 6G wireless networks
- Beyond diagonal-IRS assisted UAVs in terahertz network utilizing twin-delayed deep deterministic policy gradient approach
- Leveraging Active and Nearly Passive Reconfigurable Intelligent Surfaces Using Deep Learning Algorithm for 6G Wireless Networks
Links
- ORCID https://orcid.org/0000-0002-6969-5627
- Google Scholar https://scholar.google.com/citations?user=krQd_F8AAAAJ&hl=en
- Scopus https://www.scopus.com/authid/detail.uri?authorId=36701204400