Current students


AGHAZADEH AYOUBI REZACycle: XXXVI

Section: Telecommunications
Advisor: SPAGNOLINI UMBERTO
Tutor: CESANA MATTEO

Major Research topic:
Implementation of control and configuration algorithms for Reconfigurable Intelligent Surfaces

Abstract:
Beyond the 5G networks, require different technologies and/or technics to not only increase the rate and spectral efficiency even higher, but also to enable new functionalities like the control of autonomous driving/drones with very high reliability, and to enable virtual reality and augmented reality over the internet. Reflective intelligent surfaces which are one of the promising technologies operate based on the generalized Snell’s law by changing the impedance of a surface seen by the incident wave and manipulating the angle of reflection. These surfaces would i) enhance the coverage and rate of cell edge users or populated areas by forming hotspots, and serving rate hungry users ii) increasing the secrecy rate by nulling the unwanted users, iii) help the network to better localize the users iv) enable a more reliable autonomous driving by reducing the outage areas and the probability of blockage and many other applications with a rather low cost.
There is a need for vast research related to the RIS as this topic is still at its infancy. The goal of this Ph.D. research is to find/design the most correct propagation channel model and channel estimation method as an initial basis and tool for different research. This research includes i) calculation of the position and the required number of RISs in a given area and implementation of a comprehensive model and algorithm to find the best planning strategy based on throughput and fairness, not only by using the random deployment of the position of the users and RIS and antennas but also based on stochastic knowledge of the geometry of a city ii) efficient and fast phase configuration of the RIS based on deep reinforcement learning algorithms fused by a priori geometric information data of the transmitter and users iii) optimum resource management, based on ML algorithms iv) implementation of efficient algorithms for controlling the meta-surface to operate as a reflecting surface and also as a transmitting/refracting surface, that could enable serving also the indoor users.