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Séminaire ICI : Nasim Ferdosian

Titre du séminaire et oratrice

Cognitive Data-Driven Radio Resource Management for Sliced Services in 5G Networks

Nasim Ferdosian (ETIS, post-doctorante)

Date et lieu

Mardi 21 janvier 2020, 14h30

ENSEA, salle 384

Abstract

Future intelligent wireless cellular networks, which provide nearly-instantaneous, ultra-reliable and unlimited safe connectivity for vertical services, associated with multiple network slices, will be globally data-driven networks. In 5G networks, a dense heterogeneous architecture of various cells, diversified requirements of different services and high dynamicity of network and user conditions, causing much uncertainty and high cost of information acquisition and computations, make radio resource management more complicated. Cognitive data-driven Radio Resource Management is going to tackle these challenges and support the efficient delivery of heterogeneous traffic of sliced services. The objective is to meet network slice KPIs and provide fair resource sharing for all slices.

Bio

Nasim Ferdosian is a PostDoctoral researcher in ETIS lab at ENSEA. She was a PostDoctoral research fellow in the Communication Systems Department at EURECOM, involved in several European H2020 projects on 5G and network slicing, in 2018-2019. She was also a PostDoctoral researcher at Dublin City University, and an associate researcher with NEWTON EU H2020 Project in 2017-2018. She received her Ph.D. degree in Computer Science from University Putra Malaysia in 2017 and was awarded Fundamental Research Grant by the Malaysian Ministry of Higher Education. She obtained an M.Tech. degree in Information Technology and Computer Engineering with distinction from Jawaharlal Nehru Technological University, in 2011. Her current research interests are mainly focused on the wireless network optimization, data-driven network control & management, Artificial Intelligence enabled networking, and Machine Learning for next-generation mobile networks.

https://www.researchgate.net/profile/Nasim_Ferdosian

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