11 resultados para multi-user setting

em AMS Tesi di Dottorato - Alm@DL - Università di Bologna


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In rural and isolated areas without cellular coverage, Satellite Communication (SatCom) is the best candidate to complement terrestrial coverage. However, the main challenge for future generations of wireless networks will be to meet the growing demand for new services while dealing with the scarcity of frequency spectrum. As a result, it is critical to investigate more efficient methods of utilizing the limited bandwidth; and resource sharing is likely the only choice. The research community’s focus has recently shifted towards the interference management and exploitation paradigm to meet the increasing data traffic demands. In the Downlink (DL) and Feedspace (FS), LEO satellites with an on-board antenna array can offer service to numerous User Terminals (UTs) (VSAT or Handhelds) on-ground in FFR schemes by using cutting-edge digital beamforming techniques. Considering this setup, the adoption of an effective user scheduling approach is a critical aspect given the unusually high density of User terminals on the ground as compared to the on-board available satellite antennas. In this context, one possibility is that of exploiting clustering algorithms for scheduling in LEO MU-MIMO systems in which several users within the same group are simultaneously served by the satellite via Space Division Multiplexing (SDM), and then these different user groups are served in different time slots via Time Division Multiplexing (TDM). This thesis addresses this problem by defining a user scheduling problem as an optimization problem and discusses several algorithms to solve it. In particular, focusing on the FS and user service link (i.e., DL) of a single MB-LEO satellite operating below 6 GHz, the user scheduling problem in the Frequency Division Duplex (FDD) mode is addressed. The proposed State-of-the-Art scheduling approaches are based on graph theory. The proposed solution offers high performance in terms of per-user capacity, Sum-rate capacity, SINR, and Spectral Efficiency.

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This dissertation is devoted to the study of non-normal (modal) systems for deontic logics, both on the propositional level, and on the first order one. In particular we developed our study the Multi-relational setting that generalises standard Kripke Semantics. We present new completeness results concerning the semantic setting of several systems which are able to handle normative dilemmas and conflicts. Although primarily driven by issues related to the legal and moral field, these results are also relevant for the more theoretical field of Modal Logic itself, as we propose a syntactical, and semantic study of intermediate systems between the classical propositional calculus CPC and the minimal normal modal logic K.

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This work has been realized by the author in his PhD course in Electronics, Computer Science and Telecommunication at the University of Bologna, Faculty of Engineering, Italy. The subject of this thesis regards important channel estimation aspects in wideband wireless communication systems, such as echo cancellation in digital video broadcasting systems and pilot aided channel estimation through an innovative pilot design in Multi-Cell Multi-User MIMO-OFDM network. All the documentation here reported is a summary of years of work, under the supervision of Prof. Oreste Andrisano, coordinator of Wireless Communication Laboratory - WiLab, in Bologna. All the instrumentation that has been used for the characterization of the telecommunication systems belongs to CNR (National Research Council), CNIT (Italian Inter-University Center), and DEIS (Dept. of Electronics, Computer Science, and Systems). From November 2009 to May 2010, the author spent his time abroad, working in collaboration with DOCOMO - Communications Laboratories Europe GmbH (DOCOMO Euro-Labs) in Munich, Germany, in the Wireless Technologies Research Group. Some important scientific papers, submitted and/or published on IEEE journals and conferences have been produced by the author.

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This thesis deal with the design of advanced OFDM systems. Both waveform and receiver design have been treated. The main scope of the Thesis is to study, create, and propose, ideas and novel design solutions able to cope with the weaknesses and crucial aspects of modern OFDM systems. Starting from the the transmitter side, the problem represented by low resilience to non-linear distortion has been assessed. A novel technique that considerably reduces the Peak-to-Average Power Ratio (PAPR) yielding a quasi constant signal envelope in the time domain (PAPR close to 1 dB) has been proposed.The proposed technique, named Rotation Invariant Subcarrier Mapping (RISM),is a novel scheme for subcarriers data mapping,where the symbols belonging to the modulation alphabet are not anchored, but maintain some degrees of freedom. In other words, a bit tuple is not mapped on a single point, rather it is mapped onto a geometrical locus, which is totally or partially rotation invariant. The final positions of the transmitted complex symbols are chosen by an iterative optimization process in order to minimize the PAPR of the resulting OFDM symbol. Numerical results confirm that RISM makes OFDM usable even in severe non-linear channels. Another well known problem which has been tackled is the vulnerability to synchronization errors. Indeed in OFDM system an accurate recovery of carrier frequency and symbol timing is crucial for the proper demodulation of the received packets. In general, timing and frequency synchronization is performed in two separate phases called PRE-FFT and POST-FFT synchronization. Regarding the PRE-FFT phase, a novel joint symbol timing and carrier frequency synchronization algorithm has been presented. The proposed algorithm is characterized by a very low hardware complexity, and, at the same time, it guarantees very good performance in in both AWGN and multipath channels. Regarding the POST-FFT phase, a novel approach for both pilot structure and receiver design has been presented. In particular, a novel pilot pattern has been introduced in order to minimize the occurrence of overlaps between two pattern shifted replicas. This allows to replace conventional pilots with nulls in the frequency domain, introducing the so called Silent Pilots. As a result, the optimal receiver turns out to be very robust against severe Rayleigh fading multipath and characterized by low complexity. Performance of this approach has been analytically and numerically evaluated. Comparing the proposed approach with state of the art alternatives, in both AWGN and multipath fading channels, considerable performance improvements have been obtained. The crucial problem of channel estimation has been thoroughly investigated, with particular emphasis on the decimation of the Channel Impulse Response (CIR) through the selection of the Most Significant Samples (MSSs). In this contest our contribution is twofold, from the theoretical side, we derived lower bounds on the estimation mean-square error (MSE) performance for any MSS selection strategy,from the receiver design we proposed novel MSS selection strategies which have been shown to approach these MSE lower bounds, and outperformed the state-of-the-art alternatives. Finally, the possibility of using of Single Carrier Frequency Division Multiple Access (SC-FDMA) in the Broadband Satellite Return Channel has been assessed. Notably, SC-FDMA is able to improve the physical layer spectral efficiency with respect to single carrier systems, which have been used so far in the Return Channel Satellite (RCS) standards. However, it requires a strict synchronization and it is also sensitive to phase noise of local radio frequency oscillators. For this reason, an effective pilot tone arrangement within the SC-FDMA frame, and a novel Joint Multi-User (JMU) estimation method for the SC-FDMA, has been proposed. As shown by numerical results, the proposed scheme manages to satisfy strict synchronization requirements and to guarantee a proper demodulation of the received signal.

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The deployment of ultra-dense networks is one of the most promising solutions to manage the phenomenon of co-channel interference that affects the latest wireless communication systems, especially in hotspots. To meet the requirements of the use-cases and the immense amount of traffic generated in these scenarios, 5G ultra-dense networks are being deployed using various technologies, such as distributed antenna system (DAS) and cloud-radio access network (C-RAN). Through these centralized densification schemes, virtualized baseband processing units coordinate the distributed access points and manage the available network resources. In particular, link adaptation techniques are shown to be fundamental to overall system operation and performance enhancement. The core of this dissertation is the result of an analysis and a comparison of dynamic and adaptive methods for modulation and coding scheme (MCS) selection applied to the latest mobile telecommunications standards. A novel algorithm based on the proportional-integral-derivative (PID) controller principles and block error rate (BLER) target has been proposed. Tests were conducted in a 4G and 5G system level laboratory and, by means of a channel emulator, the performance was evaluated for different channel models and target BLERs. Furthermore, due to the intrinsic sectorization of the end-users distribution in the investigated scenario, a preliminary analysis on the joint application of users grouping algorithms with multi-antenna and multi-user techniques has been performed. In conclusion, the importance and impact of other fundamental physical layer operations, such as channel estimation and power control, on the overall end-to-end system behavior and performance were highlighted.

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Amid the remarkable growth of innovative technologies, particularly immersive technologies like Extended Reality (XR) (comprising of Virtual Reality (VR), Augmented Reality (AR) & Mixed Reality (MR)), a transformation is unfolding in the way we collaborate and interact. The current research takes the initiative to explore XR’s potential for co-creation activities and proposes XR as a future co-creation platform. It strives to develop a XR-based co-creation system, actively engage stakeholders in the co-creation process, with the goal of enhancing their creative businesses. The research leverages XR tools to investigate how they can enhance digital co-creation methods and determine if the system facilitates efficient and effective value creation during XR-based co-creation sessions. In specific terms, the research probes into whether the XR-based co-creation method and environment enhances the quality and novelty of ideas, reduce communication challenges by providing better understanding of the product, problem or process and optimize the process in terms of reduction in time and costs. The research introduces a multi-user, multi-sensory collaborative and interactive XR platform that adapts to various use-case scenarios. This thesis also presents the user testing performed to collect both qualitative and quantitative data, which serves to substantiate the hypothesis. What sets this XR system apart is its incorporation of fully functional prototypes into a mixed reality environment, providing users with a unique dimension within an immersive digital landscape. The outcomes derived from the experimental studies demonstrate that XR-based co-creation surpasses conventional desktop co-creation methods and remarkably, the results are even comparable to a full mock-up test. In conclusion, the research underscores that the utilization of XR as a tool for co-creation generates substantial value. It serves as a method that enhances the process, an environment that fosters interaction and collaboration, and a platform that equips stakeholders with the means to engage effectively.

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Machine (and deep) learning technologies are more and more present in several fields. It is undeniable that many aspects of our society are empowered by such technologies: web searches, content filtering on social networks, recommendations on e-commerce websites, mobile applications, etc., in addition to academic research. Moreover, mobile devices and internet sites, e.g., social networks, support the collection and sharing of information in real time. The pervasive deployment of the aforementioned technological instruments, both hardware and software, has led to the production of huge amounts of data. Such data has become more and more unmanageable, posing challenges to conventional computing platforms, and paving the way to the development and widespread use of the machine and deep learning. Nevertheless, machine learning is not only a technology. Given a task, machine learning is a way of proceeding (a way of thinking), and as such can be approached from different perspectives (points of view). This, in particular, will be the focus of this research. The entire work concentrates on machine learning, starting from different sources of data, e.g., signals and images, applied to different domains, e.g., Sport Science and Social History, and analyzed from different perspectives: from a non-data scientist point of view through tools and platforms; setting a problem stage from scratch; implementing an effective application for classification tasks; improving user interface experience through Data Visualization and eXtended Reality. In essence, not only in a quantitative task, not only in a scientific environment, and not only from a data-scientist perspective, machine (and deep) learning can do the difference.

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Biomedical analyses are becoming increasingly complex, with respect to both the type of the data to be produced and the procedures to be executed. This trend is expected to continue in the future. The development of information and protocol management systems that can sustain this challenge is therefore becoming an essential enabling factor for all actors in the field. The use of custom-built solutions that require the biology domain expert to acquire or procure software engineering expertise in the development of the laboratory infrastructure is not fully satisfactory because it incurs undesirable mutual knowledge dependencies between the two camps. We propose instead an infrastructure concept that enables the domain experts to express laboratory protocols using proper domain knowledge, free from the incidence and mediation of the software implementation artefacts. In the system that we propose this is made possible by basing the modelling language on an authoritative domain specific ontology and then using modern model-driven architecture technology to transform the user models in software artefacts ready for execution in a multi-agent based execution platform specialized for biomedical laboratories.

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Chlorinated solvents are the most ubiquitous organic contaminants found in groundwater since the last five decades. They generally reach groundwater as Dense Non-Aqueous Phase Liquid (DNAPL). This phase can migrate through aquifers, and also through aquitards, in ways that aqueous contaminants cannot. The complex phase partitioning to which chlorinated solvent DNAPLs can undergo (i.e. to the dissolved, vapor or sorbed phase), as well as their transformations (e.g. degradation), depend on the physico-chemical properties of the contaminants themselves and on features of the hydrogeological system. The main goal of the thesis is to provide new knowledge for the future investigations of sites contaminated by DNAPLs in alluvial settings, proposing innovative investigative approaches and emphasizing some of the key issues and main criticalities of this kind of contaminants in such a setting. To achieve this goal, the hydrogeologic setting below the city of Ferrara (Po plain, northern Italy), which is affected by scattered contamination by chlorinated solvents, has been investigated at different scales (regional and site specific), both from an intrinsic (i.e. groundwater flow systems) and specific (i.e. chlorinated solvent DNAPL behavior) point of view. Detailed investigations were carried out in particular in one selected test-site, known as “Caretti site”, where high-resolution vertical profiling of different kind of data were collected by means of multilevel monitoring systems and other innovative sampling and analytical techniques. This allowed to achieve a deep geological and hydrogeological knowledge of the system and to reconstruct in detail the architecture of contaminants in relationship to the features of the hosting porous medium. The results achieved in this thesis are useful not only at local scale, e.g. employable to interpret the origin of contamination in other sites of the Ferrara area, but also at global scale, in order to address future remediation and protection actions of similar hydrogeologic settings.

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This doctoral thesis focuses on the study of historical shallow landslide activity over time in response to anthropogenic forcing on land use, through the compilation of multi-temporal landslide inventories. The study areas, located in contrasting settings and characterized by different history of land-cover changes, include the Sillaro River basin (Italy) and the Tsitika and Eve River basins (coastal British Columbia). The Sillaro River basin belongs to clay-dominated settings, characterized by extensive badland development, and dominated by earth slides and earthflows. Here, forest removal began in the Roman period and has been followed by agricultural land abandonment and natural revegetation in recent time. By contrast, the Tsitika-Eve River basins are characterized by granitic and basaltic lithologies, and dominated by debris slides, debris flows and debris avalanches. In this setting, anthropogenic impacts started in 1960’s and have involved logging operation. The thesis begins with an introductory chapter, followed by a methodological section, where a multi-temporal mapping approach is proposed and tested at four landslide sites of the Sillaro River basin. Results, in terms of inventory completeness in time and space, are compared against the existing region-wide Emilia-Romagna inventory. This approach is then applied at the Sillaro River basin scale, where the multi-temporal inventory obtained is used to investigate the landslide activity in relation to historical land cover changes across geologic domains and in relation to hydro-meteorological forcing. Then, the impact of timber harvesting and road construction on landslide activity and sediment transfer in the Tsitika-Eve River basins is investigated, with a focus on the controls that interactions between landscape morphometry and cutblock location may have on landslide size-frequency relations. The thesis ends with a summary of the main findings and discusses advantages and limitations associated with the compilation of multi-temporal inventories in the two settings during different periods of human-driven, land-cover dynamics.

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Amid the trend of rising health expenditure in developed economies, changing the healthcare delivery models is an important point of action for service regulators to contain this trend. Such a change is mostly induced by either financial incentives or regulatory tools issued by the regulators and targeting service providers and patients. This creates a tripartite interaction between service regulators, professionals, and patients that manifests a multi-principal agent relationship, in which professionals are agents to two principals: regulators and patients. This thesis is concerned with such a multi-principal agent relationship in healthcare and attempts to investigate the determinants of the (non-)compliance to regulatory tools in light of this tripartite relationship. In addition, the thesis provides insights into the different institutional, economic, and regulatory settings, which govern the multi-principal agent relationship in healthcare in different countries. Furthermore, the thesis provides and empirically tests a conceptual framework of the possible determinants of (non-)compliance by physicians to regulatory tools issued by the regulator. The main findings of the thesis are first, in a multi-principal agent setting, the utilization of financial incentives to align the objectives of professionals and the regulator is important but not the only solution. This finding is based on the heterogeneity in the financial incentives provided to professionals in different health markets, which does not provide a one-size-fits-all model of financial incentives to influence clinical decisions. Second, soft law tools as clinical practice guidelines (CPGs) are important tools to mitigate the problems of the multi-principal agent setting in health markets as they reduce information asymmetries while preserving the autonomy of professionals. Third, CPGs are complex and heterogeneous and so are the determinants of (non-)compliance to them. Fourth, CPGs work but under conditions. Factors such as intra-professional competition between service providers or practitioners might lead to non-compliance to CPGs – if CPGs are likely to reduce the professional’s utility. Finally, different degrees of soft law mandate have different effects on providers’ compliance. Generally, the stronger the mandate, the stronger the compliance, however, even with a strong mandate, drivers such as intra-professional competition and co-management of patients by different professionals affected the (non-)compliance.