Performance analysis of ray-tracing assisted beamforming techniques for future mm-wave wireless systems.

Il progetto di tesi riguarda principalmente la progettazione di moderni sistemi wireless, come 5G o WiGig, operanti a onde millimetriche, attraverso lo studio di una tecnica avanzata detta Beamforming, che, grazie all'utilizzo di antenne direttive e compatte, permette di superare limiti di link budget dovuti alle alte frequenze e introdurre inoltre diversità spaziale alla comunicazione. L'obiettivo principale del lavoro è stato quello di valutare, tramite simulazioni numeriche, le prestazioni di alcuni diversi schemi di Beamforming integrando come tool di supporto un programma di Ray Tracing capace di fornire le principali informazioni riguardo al canale radio. Con esso infatti è possibile sia effettuare un assessment generale del Beamforming stesso, ma anche formulare i presupposti per innovative soluzioni, chiamate RayTracing-assisted- Beamforming, decisamente promettenti per futuri sviluppi così come confermato dai risultati.

An experimental and modelling study of the capture of CO2 from gas mixtures with different techniques, with focus on multicomponent effects.

In the present work, the deviations in the solubility of CO2, CH4, and N2 at 30 °c in the mixed gases (CO2/CH4) and (CO2/N2) from the pure gas behavior were studied using the dual-mode model over a wide range of equilibrium composition and pressure values in two glassy polymers. The first of which was PI-DAR which is the polyimide formed by the reaction between 4, 6-diaminoresorcinol dihydrochloride (DAR-Cl) and 2, 2’-bis-(3, 4-dicarboxyphenyl) hexafluoropropane dianhydride (6FDA). The other glassy polymer was TR-DAR which is the corresponding thermally rearranged polymer of PI-DAR. Also, mixed gas sorption experiments for the gas mixture (CO2/CH4) in TR-DAR at 30°c took place in order to assess the degree of accuracy of the dual-mode model in predicting the true mixed gas behavior. The experiments were conducted on a pressure decay apparatus coupled with a gas chromatography column. On the other hand, the solubility of CO2 and CH4 in two rubbery polymers at 30⁰c in the mixed gas (CO2/CH4) was modelled using the Lacombe and Sanchez equation of state at various values of equilibrium composition and pressure. These two rubbery polymers were cross-linked poly (ethylene oxide) (XLPEO) and poly (dimethylsiloxane) (PDMS). Moreover, data about the sorption of CO2 and CH4 in liquid methyl dietahnolamine MDEA that was collected from literature65-67 was used to determine the deviations in the sorption behavior in the mixed gas from that in the pure gases. It was observed that the competition effects between the penetrants were prevailing in the glassy polymers while swelling effects were predominant in the rubbery polymers above a certain value of the fugacity of CO2. Also, it was found that the dual-mode model showed a good prediction of the sorption of CH4 in the mixed gas for small pressure values but in general, it failed to predict the actual sorption of the penetrants in the mixed gas.

Studies of CMS data access patterns with machine learning techniques

This thesis presents a study of the Grid data access patterns in distributed analysis in the CMS experiment at the LHC accelerator. This study ranges from the deep analysis of the historical patterns of access to the most relevant data types in CMS, to the exploitation of a supervised Machine Learning classification system to set-up a machinery able to eventually predict future data access patterns - i.e. the so-called dataset “popularity” of the CMS datasets on the Grid - with focus on specific data types. All the CMS workflows run on the Worldwide LHC Computing Grid (WCG) computing centers (Tiers), and in particular the distributed analysis systems sustains hundreds of users and applications submitted every day. These applications (or “jobs”) access different data types hosted on disk storage systems at a large set of WLCG Tiers. The detailed study of how this data is accessed, in terms of data types, hosting Tiers, and different time periods, allows to gain precious insight on storage occupancy over time and different access patterns, and ultimately to extract suggested actions based on this information (e.g. targetted disk clean-up and/or data replication). In this sense, the application of Machine Learning techniques allows to learn from past data and to gain predictability potential for the future CMS data access patterns. Chapter 1 provides an introduction to High Energy Physics at the LHC. Chapter 2 describes the CMS Computing Model, with special focus on the data management sector, also discussing the concept of dataset popularity. Chapter 3 describes the study of CMS data access patterns with different depth levels. Chapter 4 offers a brief introduction to basic machine learning concepts and gives an introduction to its application in CMS and discuss the results obtained by using this approach in the context of this thesis.

Study of the second hyperpolarizability of poly(3-alkylthiophenes) using the third-harmonic scattering technique

During the past years, the considerable need in the domain of communications for more potent photonic devices has focused the research activities into the nonlinear optical (NLO) materials which can be used for modern optical switches. In this regard, a lot of research activities are focused on the organic materials and conjugated polymers which offer more advantages compared to the inorganic ones. On this matter, poly(3-alkylthiophene) (P3AT), an organic conjugated polymer, can be investigated as potential optical material with in particular the focus on the NLO properties such as the first- and second-hyperpolarizability, β and γ respectively. The activities carried out at the Laboratory of Polymer Synthesis of the KU Leuven, during the master's thesis work, focused on the study of conjugated polymers in order to evaluate their NLO properties for the future purpose of applications in optical systems. In particular, three series of polythiophenes functionalized with an alkyl side chain in the 3-position were synthesized: poly(3-hexylthiophene) (P3HT), poly[3-(2-ethylhexyl)thiophene] (P3EHT) and random copolymer of the two regio-isomers of P3HT. They were made in order to study the influence of molar mass, branching and regio-irregularity on the γ-value. The Kumada catalyst transfer condensative polymerization (KCTCP) and the Pd(RuPhos)-protocol were used for the polymerizations in order to have control over the molar mass of the growing chain and consequently to obtain well-defined and reproducible materials. The P3AT derivatives obtained were characterized by gel permeation chromatography (GPC), spectroscopic techniques (1H-NMR, UV-Vis) and the γ-value was investigated using the third-harmonic scattering (THS) technique. In particular, the THS technique is useful to investigate the optical behavior of the series of polymers in solution.

Graph-based User Scheduling for MIMO LEO-based Satellite Communication Systems

The study of the user scheduling problem in a Low Earth Orbit (LEO) Multi-User MIMO system is the objective of this thesis. With the application of cutting-edge digital beamforming algorithms, a LEO satellite with an antenna array and a large number of antenna elements can provide service to many user terminals (UTs) in full frequency reuse (FFR) schemes. Since the number of UTs on-ground are many more than the transmit antennas on the satellite, user scheduling is necessary. Scheduling can be accomplished by grouping users into different clusters: users within the same cluster are multiplexed and served together via Space Division Multiple Access (SDMA), i.e., digital beamforming or Multi-User MIMO techniques; the different clusters of users are then served on different time slots via Time Division Multiple Access (TDMA). The design of an optimal user grouping strategy is known to be an NP-complete problem which can be solved only through exhaustive search. In this thesis, we provide a graph-based user scheduling and feed space beamforming architecture for the downlink with the aim of reducing user inter-beam interference. The main idea is based on clustering users whose pairwise great-circle distance is as large as possible. First, we create a graph where the users represent the vertices, whereas an edge in the graph between 2 users exists if their great-circle distance is above a certain threshold. In the second step, we develop a low complex greedy user clustering technique and we iteratively search for the maximum clique in the graph, i.e., the largest fully connected subgraph in the graph. Finally, by using the 3 aforementioned power normalization techniques, a Minimum Mean Square Error (MMSE) beamforming matrix is deployed on a cluster basis. The suggested scheduling system is compared with a position-based scheduler, which generates a beam lattice on the ground and randomly selects one user per beam to form a cluster.

Axis control optimization: autotuning techniques and frequency response analysis of industrial mechatronic systems

In the field of industrial automation, there is an increasing need to use optimal control systems that have low tracking errors and low power and energy consumption. The motors we are dealing with are mainly Permanent Magnet Synchronous Motors (PMSMs), controlled by 3 different types of controllers: a position controller, a speed controller, and a current controller. In this thesis, therefore, we are going to act on the gains of the first two controllers by going to find, through the TwinCAT 3 software, what might be the best set of parameters. To do this, starting with the default parameters recommended by TwinCAT, two main methods were used and then compared: the method of Ziegler and Nichols, which is a tabular method, and advanced tuning, an auto-tuning software method of TwinCAT. Therefore, in order to analyse which set of parameters was the best,several experiments were performed for each case, using the Motion Control Function Blocks. Moreover, some machines, such as large robotic arms, have vibration problems. To analyse them in detail, it was necessary to use the Bode Plot tool, which, through Bode plots, highlights in which frequencies there are resonance and anti-resonance peaks. This tool also makes it easier to figure out which and where to apply filters to improve control.