Short biography

I graduated with a Bachelor's degree in Electronic Engineering from the University of Nigeria, Nsukka in 2014. After graduation, I worked 4-years (2015 - 2019) with Nokia Networks in Nigeria as a Network Operations Engineer/Analyst. To further my academics, I joined the Smart Telecoms and Sensing Networks (SMARTNET) Erasmus Masters Programme in 2019. I did my 1st-year of masters in Informatics and Telecommunication at the University of Athens, Greece, and my 2nd-year in Optical Networks and Photonics Systems at Telecom SudParis/Telecom Paris Tech, France. My MSc thesis was written during my 6-months research internship at Nokia Bell Labs, Paris-Saclay, France. I graduated from my MSc programme in September 2021. Afterwards, I joined the Universitat Politècnica De Catalunya (UPC) in Barcelona, Spain, for a PhD researcher position in February, 2022. The position is part of the Marie Curie 5GSMARTFACT project, whose objective is to study, develop, optimize and assess the deployment of 5G networks targeting IIoT requirements in factory environments. My PhD topic is 'Slicing for 5G dense radio networks in smart factories'. I will be carrying out part of research in Nokia Bell Labs, Aalborg, Denmark and Siradel, Rennes, France.

Short description of project objectives

My research aims to develop technologies to enable simultaneous 5G-and-beyond mixed services ultra-reliable low latency communications (URLLC), massive machine-type communications (mMTC) and enhanced mobile broadband communications (eMBB) in an Industry 4.0 environment, like bounded latency AR/VR devices and low-rate IoT devices. In addition to the conventional dense access points deployments, we plan its coexistence with controllable reconfigurable intelligent surfaces (RIS) and massive distributed antennas. We will adopt approaches that account for:

• The development of mathematical models describing uncertainties in propagation scenarios (channel state, interference, traffic dynamics, etc.) and of the traffic leading to an accurate evaluation of outage coverage, latency, capacity and packet loss.

• The use of optimization and machine learning-based strategies in the dynamic optimization of resources based on grant-based/grant-free protocols.

• The characterization of trade-offs in slicing eMMB, mMTC and URLLC traffic, in unicast and multicast modes and derivation of procedures to manage slices in a dynamic, robust and energy-efficient way, ensuring pre-defined outage, coverage, reliability and bitrate performance for mixed services.

• Addressing critical mobility scenarios and propose dual active protocol stack with AI-based predictive solutions to considerably reduce interruption times and radio link failures.

• So far, my work has been focused mainly on studying concepts explicitly related to my research objectives some of which includes; URLLC-6G, MIMO channels, resource allocation and optimization in multi-users scenario, and RIS.