Abdelfatteh Haidine

Université Chouaib DoukkaliMorocco

Dr.Ing. Abdelfatteh Haidine received his Ph.D. in 2008 from the Technische Universität Dresden, Germany, with a focus on the planning and optimization of telecommunications networks. He worked as a consultant and manager for the deployment of smart metering systems and smart grid applications. Currently, he is an assistant professor for wireless/mobile communications and intelligent systems with the Laboratory of Information Technologies, National School of Applied Sciences, Morocco. His research interests include different issues related to Machine-to-Machine (M2M) and Internet-of-Things (IoT) communications, networking technologies for smart domains: smart maritime port, smart city and smart grid applications, and so on. This covers LPWA networks and their techno-economical aspects. Dr. Haidine also deals with the application of combinatorial optimization as well as the Game Theory paradigm in network planning/migration and resources allocation in broadband mobile networks. In addition, he investigates artificial intelligence and machine learning in optimization procedures/paradigms.

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Latest work with IntechOpen by Abdelfatteh Haidine

The deployment of 4G/LTE (Long-Term Evolution) mobile networks has solved the major challenge of high capacities to build a real broadband mobile internet. This was possible mainly through a very strong physical layer and flexible network architecture. However, bandwidth-hungry services such as virtual reality (VR) and augmented reality (AR), have been developed in an unprecedented way. Furthermore, mobile networks are facing other new services with extreme demand for greater reliability and almost zero-latency performance, like vehicle communications and the Internet of Vehicles (IoV). Therefore, industries and researchers are investigating new physical layers and softwarization techniques and including more intelligence in 5G and beyond 5G (B5G/6G). This book discusses some of these softwarization techniques, such as fog computing, cloud computing, and artificial intelligence (AI) and machine learning (ML). It also presents use cases showing practical aspects from 5G deployment scenarios, where other communications technologies will co-habit to build the landscape of next-generation mobile networks (NGMNs).

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