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.

Satellite IoT: a Study and Performance Analysis of GEO and LEO Systems

The study is divided into two main part: one focused on the GEO Satellite IoT and the other on the LEO Satellite IoT. Concerning the GEO Satellite IoT, the activity has been developed in the context of EUMETSAT Data Collection Service (DCS) by investigating the performance at the receiver within challenging scenarios. DCS are provided by several GEO Satellite operators, giving almost total coverage around the world. In this study firstly an overview of the DCS end-to-end architecture is given followed by a detailed description of both the tools used for the simulations: the DCP-TST (message generator and transmitter) and the DCP-RX (receiver). After generating several test messages, the performances have been evaluated with the addition of impairments (CW and sweeping interferences) and considerations in terms of BER and Good Messages are produced. Furthermore, a study on the PLL System is also conducted together with evaluations on the effectiveness of tuning the PLL Bw on the overall performance. Concerning the LEO Satellite IoT, the activity was carried out in the framework of the ASI Bidirectional IoT Satellite Service (BISS) Project. The elaborate covers a survey about the possible services that the project can accomplish and a technical analysis on the uplink MA. In particular, the LR-FHSS is proved to be a valid alternative for the uplink through an extensive analysis on its Network capacity and through the study of an analytic model for Success Probability with its Matlab implementation.

Performance analysis of different sensing techniques in Cognitive Radio Networks.

The spectrum of radiofrequency is distributed in such a way that it is fixed to certain users called licensed users and it cannot be used by unlicensed users even though the spectrum is not in use. This inefficient use of spectrum leads to spectral holes. To overcome the problem of spectral holes and increase the efficiency of the spectrum, Cognitive Radio (CR) was used and all simulation work was done on MATLAB. Here analyzed the performance of different spectrum sensing techniques as Match filter based spectrum sensing and energy detection, which depend on various factors, systems such as Numbers of input, signal-to-noise ratio ( SNR Ratio), QPSK system and BPSK system, and different fading channels, to identify the best possible channels and systems for spectrum sensing and improving the probability of detection. The study resulted that an averaging filter being better than an IIR filter. As the number of inputs and SNR increased, the probability of detection also improved. The Rayleigh fading channel has a better performance compared to the Rician and Nakagami fading channel.

Performance Analysis of Topological Quantum Error Correcting Codes

In the last few years there has been a great development of techniques like quantum computers and quantum communication systems, due to their huge potentialities and the growing number of applications. However, physical qubits experience a lot of nonidealities, like measurement errors and decoherence, that generate failures in the quantum computation. This work shows how it is possible to exploit concepts from classical information in order to realize quantum error-correcting codes, adding some redundancy qubits. In particular, the threshold theorem states that it is possible to lower the percentage of failures in the decoding at will, if the physical error rate is below a given accuracy threshold. The focus will be on codes belonging to the family of the topological codes, like toric, planar and XZZX surface codes. Firstly, they will be compared from a theoretical point of view, in order to show their advantages and disadvantages. The algorithms behind the minimum perfect matching decoder, the most popular for such codes, will be presented. The last section will be dedicated to the analysis of the performances of these topological codes with different error channel models, showing interesting results. In particular, while the error correction capability of surface codes decreases in presence of biased errors, XZZX codes own some intrinsic symmetries that allow them to improve their performances if one kind of error occurs more frequently than the others.

An Embedded In-Cabin Lightweight High-Performance 3D Gaze Estimation System

Gaze estimation has gained interest in recent years for being an important cue to obtain information about the internal cognitive state of humans. Regardless of whether it is the 3D gaze vector or the point of gaze (PoG), gaze estimation has been applied in various fields, such as: human robot interaction, augmented reality, medicine, aviation and automotive. In the latter field, as part of Advanced Driver-Assistance Systems (ADAS), it allows the development of cutting-edge systems capable of mitigating road accidents by monitoring driver distraction. Gaze estimation can be also used to enhance the driving experience, for instance, autonomous driving. It also can improve comfort with augmented reality components capable of being commanded by the driver's eyes. Although, several high-performance real-time inference works already exist, just a few are capable of working with only a RGB camera on computationally constrained devices, such as a microcontroller. This work aims to develop a low-cost, efficient and high-performance embedded system capable of estimating the driver's gaze using deep learning and a RGB camera. The proposed system has achieved near-SOTA performances with about 90% less memory footprint. The capabilities to generalize in unseen environments have been evaluated through a live demonstration, where high performance and near real-time inference were obtained using a webcam and a Raspberry Pi4.