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 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.

Performance of LTE-V2V for Cooperative Awareness

The large scale development of an Intelligent Transportation System is very close. The main component of such a smart environment is the network that provides connectivity for all vehicles. Public safety is the most demanding application because requires a fast, reliable and secure communication. Although IEEE 802.11p is presently the only full wireless standard for vehicular communications, recent advancements in 3GPP LTE provide support to direct communications and the ongoing activities are also addressing the vehicle to vehicle case. This thesis focuses on the resource allocation procedures and performance of LTE-V2V. To this aim, a MATLAB simulator has been implemented and results have been obtained adopting different mobility models for both in-coverage and out-of-coverage scenarios.

Voice conversion with pre-trained representations for audio anonymization

The recording and processing of voice data raises increasing privacy concerns for users and service providers. One way to address these issues is to move processing on the edge device closer to the recording so that potentially identifiable information is not transmitted over the internet. However, this is often not possible due to hardware limitations. An interesting alternative is the development of voice anonymization techniques that remove individual speakers characteristics while preserving linguistic and acoustic information in the data. In this work, a state-of-the-art approach to sequence-to-sequence speech conversion, ini- tially based on x-vectors and bottleneck features for automatic speech recognition, is explored to disentangle the two acoustic information using different pre-trained speech and speakers representation. Furthermore, different strategies for selecting target speech representations are analyzed. Results on public datasets in terms of equal error rate and word error rate show that good privacy is achieved with limited impact on converted speech quality relative to the original method.

Quantum error correction with the IBM quantum experience

Mentre si svolgono operazioni su dei qubit, possono avvenire vari errori, modificando così l’informazione da essi contenuta. La Quantum Error Correction costruisce algoritmi che permettono di tollerare questi errori e proteggere l’informazione che si sta elaborando. Questa tesi si focalizza sui codici a 3 qubit, che possono correggere un errore di tipo bit-flip o un errore di tipo phase-flip. Più precisamente, all’interno di questi algoritmi, l’attenzione è posta sulla procedura di encoding, che punta a proteggere meglio dagli errori l’informazione contenuta da un qubit, e la syndrome measurement, che specifica su quale qubit è avvenuto un errore senza alterare lo stato del sistema. Inoltre, sfruttando la procedura della syndrome measurement, è stata stimata la probabilità di errore di tipo bit-flip e phase-flip su un qubit attraverso l’utilizzo della IBM quantum experience.