This thesis investigates the fundamental performance of Hierarchical Non-Terrestrial Networks for the 6th generation (6G). 6G communication research is currently focus- ing on non-terrestrial networks (NTNs) to promote ubiquitous and ultra-high-capacity global connectivity. Specifically, multi-layered hierarchical networks, i.e., the orches- tration among different aerial/space platforms, including Unmanned Aerial Vehicles (UAVs), High Altitude Platforms (HAPs), and satellites co-operating at different al- titudes, currently represents one the most attractive technological options to solve coverage and latency constraints associated with the NTN paradigm. However, there are still several issues to be resolved for proper network design. In this thesis, we in- vestigate the propagation model in air/space links and then evaluate the performance of different multi-layered non-terrestrial configurations, and then provide guidelines on the optimal working point(s) for which it is possible to achieve a good compro- mise between improved system flexibility and network performance, with respect to a baseline standalone deployment.

The next-generation (6G) networks promise to provide extended 5G capabilities with enhanced performance at high data rates, low latency, low energy consumption, and rapid adaptation. 6G networks are also expected to support the unprecedented Internet of Everything (IoE) scenarios with highly diverse requirements. With the emerging applications of autonomous driving, virtual reality, and mobile computing, achieving better performance and fulfilling the diverse requirements of 6G networks are becoming increasingly difficult due to the rapid proliferation of wireless data and heterogeneous network structures. In this regard, learning-based algorithms are naturally powerful tools to deal with the numerous data and are expected to impact the evolution of communication networks. This thesis employed learning-based approaches to enhance the performance and fulfill the diverse requirements of the next-generation intelligent networks under various network structures. Specifically, we design the trajectory of the unmanned aerial vehicle (UAV) to provide energy-efficient, high data rate, and fair service for the Internet of things (IoT) networks by employing on/off-policy reinforcement learning (RL). Thereafter, we applied a deep RL-based approach for heterogeneous traffic offloading in the space-air-ground integrated network (SAGIN) to cover the co-existing requirements of ultra-reliable low-latency communication (URLLC) traffic and enhanced mobile broadband (eMBB) traffic. Precise traffic prediction can significantly improve the performance of 6G networks in terms of intelligent network operations, such as predictive network configuration control, traffic offloading, and communication resource allocation. Therefore, we investigate the wireless traffic prediction problem in edge networks by applying a federated meta-learning approach. Lastly, we design an importance-oriented clustering-based high quality of service (QoS) system with software-defined networking (SDN) by adopting unsupervised learning.

Titre de l'écran-titre (visionné le 10 janvier 2024) / L'avènement des réseaux mobiles 6G promet de révolutionner les systèmes de communication mobile, en offrant une capacité très élevée et une faible latence. Pour exploiter pleinement le potentiel des réseaux mobiles 6G, il est essentiel de disposer d'une localisation de haute précision. L'incorporation des bandes térahertz (THz) est un facteur critique pour atteindre cette précision de localisation. Dans ce contexte, nous proposons une approche pour la localisation des terminaux d'utilisateurs dans les réseaux mobiles 6G, en tirant partie des bandes de fréquences THz. L'approche proposée est basée sur la technique de localisation par angle d'arrivée (AoA). Nous utilisons cette technique de localisation parce qu'elle offre une plus grande précision. Pour mettre en œuvre notre approche, nous utilisons des simulations avancées dans NYUSIM. Plus précisément, nous effectuons deux simulations. La première simulation émule un réseau mobile 5G dans les bandes mmWave et la seconde un réseau mobile 6G dans les bandes de fréquences THz. Les résultats montrent que les réseaux mobiles 6G sont plus performants que les réseaux mobiles 5G en termes de précision de localisation. Cette amélioration est attribuée à l'estimation plus fine du canal facilitée par les fréquences THz, ce qui permet de réduire les interférences du signal et d'améliorer la précision du positionnement. Nos résultats montrent également que les réseaux mobiles 6G nécessitent moins de puissance d'émission pour atteindre une précision de localisation similaire à celle des réseaux mobiles 5G. Cette découverte souligne le potentiel des réseaux mobiles 6G à réduire la pollution environnementale et à contribuer au développement durable. / The advent of 6G mobile networks holds immense promises for revolutionizing mobile communication systems, offering ultra-high capacity and low latency. To fully realize the potential of 6G mobile networks, high-precision localization is essential. A critical factor in achieving this localization accuracy is the incorporation of Terahertz (THz) bands. In this context, we propose an approach for localizing user terminals in 6G mobile networks leveraging THz frequency bands. The proposed approach is based on the Angle of Arrival (AoA) localization technique. We use this technique because it provides greater localization accuracy. To implement our approach, we employ advanced simulations in NYUSIM to bridge the gap between theoretical knowledge and practical applications. More specifically, we perform two simulations. The first simulation emulates a 5G mobile network in the mmWave bands, and the second one emulates a 6G mobile network in the THz frequency bands. The results show that 6G mobile networks outperform 5G mobile networks in terms of localization accuracy. This improvement is attributed to the finer channel estimation facilitated by THz frequencies, resulting in reduced signal interference and enhanced positioning accuracy. Our results also show that 6G mobile networks require less transmit power to achieve similar localization accuracy than 5G mobile networks. This finding highlights the potential of 6G mobile networks to reduce environmental pollution and contribute to sustainability.

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Future wireless networks are envisioned to support a wide range of novel use cases, and connect a massive number of people and devices in an energy efficient way. Several key enabling technologies were considered to support this vision including Internet of Things (IoT) networks, aerial and stratospheric platforms, and reconfigurable intelligent surfaces (RIS). In this dissertation, we study different problems related to the integration between these technologies. First, we propose a cost-effective framework for data collection from IoT sensors using multiple unmanned aerial vehicles (UAVs). This is achieved by effcient clustering of the sensors and optimized deployment of cluster heads (CHs). Then, the number of deployed UAVs and their trajectories will be optimized to minimize the data collection flight time. The impacts of the trajectory approach, environment type, and UAVs' altitude as well as the fairness of UAVs trajectories on the data collection process are investigated. Given that IoT nodes might have different priorities and time deadlines, and respecting the limited battery capacity of UAVs, we enhance the data collection framework to account for these practical constraints. First, an algorithm for finding the minimal number of CHs and their best locations is proposed. Then, the minimal number of UAVs and their trajectories are obtained by solving the associated capacitated vehicle routing problem. The results investigate the impacts of the selected trajectory approach, the battery capacity and time deadlines on the consumed energy, number of visited CHs, and number of deployed UAVs. Next, given the energy issue on aerial platforms, we present our vision for integrating RIS in aerial and stratospheric platforms to provide energy-efficient communications. We propose a control architecture for such integration, discuss its benefits and identify potential use cases and associated research challenges. Then, to substantiate our vision, we study the link budget of RIS-assisted communications under the specular and the scattering reflection paradigms. Specifically, we analyze the characteristics of RIS-equipped stratospheric and aerial platforms and compare their communication performance with that of RIS-assisted terrestrial networks, using standardized channel models. In addition, we derive the optimal aerial platforms placements under both reflection paradigms. The obtained results provide important insights for the design of RIS-assisted communications. For instance, given that a HAPS has a large RIS surface, it provides superior link budget performance in most studied scenarios. In contrast, the limited RIS area on UAVs and the large propagation loss in low Earth orbit (LEO) satellite communications make them unfavorable candidates for supporting terrestrial users. Then, motivated by the demonstrated potential of HAPS equipped with RIS (HAPS-RIS), we propose a solution to support the stranded users in terrestrial networks through a dedicated control station (CS) and HAPS-RIS. We refer to this approach as "beyond-cell" communications. We demonstrate that this approach works in tandem with legacy terrestrial networks to support uncovered or unserved users. Optimal transmit power and RIS unit assignment strategies for the users based on different network objectives are introduced. Furthermore, to increase the percentage of admitted users in an efficient manner, a novel resource-efficient optimization problem is formulated that maximizes the number of connected UEs, while minimizing the total power consumed by the CS and RIS. Since the resulting problem is a mixed-integer nonlinear program (MINLP), a low-complexity two-stage algorithm is developed. Finally, given the different applications and various options of HAPS payload, we envision the use of a multi-mode HAPS that can adaptively switch between different modes so as to reduce energy consumption and extend the HAPS loitering time. These modes comprise a HAPS super macro base station (HAPS-SMBS) mode for enhanced computing, caching, and communication services, a HAPS relay station (HAPS-RS) mode for active communication, and a HAPSRIS mode for passive communication. This multi-mode HAPS ensures that operations rely mostly on the passive communication payload while switching to an energy-greedy active mode only when necessary. We illustrate the envisioned multi-mode HAPS, and discuss its benefits and challenges. Then, we validate the multi-mode efficiency through a case study. At the end of the dissertation, several future research directions are proposed including hybrid orthogonal and non-orthogonal multiple access (OMA/NOMA) beyond-cell communications assisted by HAPS-RIS, configuration of RIS units on stratospheric platforms, energy management for HAPS-RIS, and supporting aerial users through terrestrial RIS.

The evolution from the fifth generation (5G) networks to 6G promises to revolution- ize connectivity, supporting a vast array of applications from high-definition video streaming and immersive augmented reality experiences to critical machine-type communications. However, this progression brings along the challenge of efficiently managing the limited radio spectrum (RF) resources to accommodate the diverse quality of service (QoS) requirements of a variety of service and user types. Another problem gaining traction with the advances of wireless communications technology is the coexistence between active communication systems and passive RF sensing operating in the same or adjacent bands. Central to addressing these challenges is the proposed application of deep reinforcement learning (DRL), which emerges as a tool for adaptive and intel- ligent radio resource management (RRM) in the face of the increasingly complex and dynamic RF system requirements. This dissertation investigates the application of DRL for service, user, and network management of advanced wireless networks operating in dedicated and shared spectrum. Through a series of innovative DRL-based frameworks and solutions to a variety of emerging RRM problems, this work contributes to the optimization of spectrum, transmission power, and band- width allocation, as well as network configuration. We contribute to the integration of cutting-edge technologies such as unmanned aerial vehicles as aerial base stations, reconfigurable intelligent sur- faces, and multi-user multiple input, multiple output systems for a seamless user experience. The core of the dissertation explores how DRL can adaptively manage spectrum resources that satisfy the QoS requirements of different 5G service classes, specifically enhanced mobile broadband and ultra-reliable low-latency communications, while also facilitating the integration of terrestrial and aerial network nodes to enhance coverage and capacity. This dissertation further extends into the domain of coexistence between active wireless communication systems and passive remote sensing technologies. We collect radiometric measurement data in a custom-built software-defined radio testbed for which we design different 5G downlink transmission patters and data sets. Based on the collected and processed data from the testbed’s radiometer, we propose a DRL-based strategy to manage 5G communications while reducing the RF interference impact on co-channel radiometric measurements. Through simulations, the proposed solution demonstrates the tradeoffs between communications and sensing operations in terms of common wireless network performance met- rics, such as sum data rate and user fairness, and brightness temperature readings obtained by the radiometer.

Next-generation wireless technologies are being actively researched to meet the growing demands for higher data rates, massive connectivity, enhanced reliability, and extended coverage. Recently, reconfigurable intelligent surfaces (RISs) and extremely large antenna arrays (ELAAs) have garnered significant attention as new physical-layer transmission technologies capable of achieving unprecedented spectral and energy efficiency gains. Consequently, RIS and ELAA are considered as promising key enabling technologies for the sixth-generation (6G) and future wireless standards.This dissertation investigates RIS and simultaneously transmitting and reflecting (STAR)-RIS assisted wireless communications, emphasizing design, optimization, and analysis across various practical settings. It presents wireless channel modelling techniques, system design aspects, fundamental performance limits/metrics, including outage probability, average achievable rate, average symbol error rate (SER), diversity order, computational complexity, and algorithmic foundations. This doctoral research also develops algorithms for optimizing RIS/STAR-RIS phase shifts and transmit power allocation in multi-user massive multiple-input multiple-output (MIMO) systems. Moreover, this dissertation characterizes unique propagation characteristics of ELAAs, and thereby impacts of visibility regions (VRs) and spatial non-stationarity in extra-large (XL) RIS communication set-ups with XL-massive MIMO base stations (BS) are analyzed.The dissertation begins with a fundamental performance analysis of RIS-assisted systems operating over Nakagami-m fading channels. It quantifies optimal phase-shifts to maximize received signal-to-noise ration (SNR) and derives the probability distribution of the SNR. The findings include closed-form expressions for outage probability, average SER, and achievable rate, demonstrating that these metrics improve as the number of RIS reflective elements increases. The study also reveals that the achievable diversity order scales linearly with the number of passive RIS elements, resulting in significant diversity gains without additional radio-frequency (RF) chains. Further investigation into STAR-RIS systems with discrete phase-shifts highlights the performance under different protocols, such as energy splitting (ES), mode switching (MS), and time splitting (TS), considering both unicast and multicast transmissions. The analysis demonstrates that employing four-bit phase-shift quantization significantly narrows the performance gap between discrete and continuous phase-shifts. Additionally, it is found that the average achievable rate and SER reach saturation levels at high transmit SNRs, influenced by power allocation coefficients at the transmitter. The dissertation also presents an achievable rate analysis and RIS phase-shift optimization for multi-cell RIS-aided massive MIMO, with for imperfect channel state information (CSI), co-channel interference, and spatially correlated fading. A statistical CSI-based transmit power allocation algorithm is proposed, reducing channel estimation overhead and ensuring user fairness. In exploring STAR-RIS aided multi-user massive MIMO systems, statistical CSI-based STAR-RIS phase-shift and transmit power optimization techniques are used to maximize composite channel gains and ensure fair user rates. The study quantifies the impacts of CSI imperfections, residual interference, and spatially correlated fading. Lastly, the effects of visibility regions in XL RIS setups are examined, deriving achievable user rates and employing phase-shift optimization to maximize user channel covariance. A max-min power allocation algorithm is utilized to address near-far user effects, ensuring system-wide user fairness. Overall, this dissertation provides comprehensive insights and advanced optimization techniques for enhancing RIS and STAR-RIS technologies in wireless communication systems.

Orientador: Cláudia Longo / Tese (doutorado) - Universidade Estadual de Campinas, Instituto de Química / Made available in DSpace on 2018-08-21T05:10:58Z (GMT). No. of bitstreams: 1 Oliveira_HaroldoGregoriode_D.pdf: 8058595 bytes, checksum: b4141a5719256524b785c37f949ee3d8 (MD5) Previous issue date: 2012 / Resumo: Eletrodos de filmes porosos contendo TiO2 e WO3 foram preparados sobre vidro revestido com SnO2:F (FTO), a partir de suspensões aquosas de TiO2 Degussa P25®, precursores de WO3, polietileno glicol e aquecimento (450°C, 30 min). As amostras de TiO2 e WO3 apresentaram máximo de absorção respectivamente em 390 e 480 nm; valores intermediários foram observados para as misturas. Os filmes de TiO2, ca. 4,5 mm, consistem de partículas esféricas interconectadas (diâmetro 25 nm) resultando em superfície porosa e excelente cobertura do substrato. A presença de H2WO4 na suspensão de TiO2 resultou no filme TiO2/WO3, com morfologia semelhante porém menos poroso. O eletrodo de WO3 apresentou cobertura não uniforme, com partículas na forma de flocos (0,1-1 mm). A deposição de TiO2 sobre o WO3 resultou no eletrodo de WO3-TiO2, de morfologia similar a do TiO2. As propriedades eletroquímicas foram investigadas em solução aquosa de Na2SO4, na ausência de luz e sob irradiação policromática. Os eletrodos apresentaram comportamento de semicondutor tipo n, com fotopotencial negativo e fotocorrente anódica; a presença do WO3 promoveu um aumento na fotocorrente. Os eletrodos foram utilizados para remediação de solução aquosa do corante rodamina 6G (10 mmol L) nas configurações de fotocatálise heterogênea (FH) e FH eletroquimicamente assistida por polarização a 0,7 V (FHE). Sob irradiação, nas 3 h iniciais, observou-se cinética de pseudo-1a ordem para o descoramento da solução; em FH, os eletrodos de WO3, TiO2 e WO3-TiO2 promoveram respectivamente a remoção de 8, 34 e 38 % do corante (constante de velocidade aparente de 0,37x10; 2,3x10 e 2,8x10 min) e, na ausência de fotocatalisador, apenas 4%. Maior eficiência foi observada em FHE; para o WO3-TiO2, p.ex., houve remoção de 44% do corante (3,2x10 min). Os eletrodos também foram utilizados para tratamento de solução aquosa do hormônio 17 a-etinilestradiol (34 mmol L); após 4 h em condições de FH e FHE, a remediação com TiO2 resultou na degradação de 38 e 48 %, enquanto que o eletrodo de TiO2/WO3 promoveu a degradação de 45 e 54 %. Ambos os eletrodos promoveram mineralização semelhante do hormônio, 15 e 19 %, para as condições de FH e FHE; na ausência de fotocatalisador, observou-se degradação de 10 % (4 % de mineralização). A oxidação fotocatalítica dos poluentes com estes eletrodos foi discutida considerando diagramas de energia; na presença de WO3, além de se obter um maior aproveitamento da radiação visível, a posição favorável das bandas de condução e de valência de ambos os semicondutores promove a separação das cargas fotogeradas, o que minimiza sua recombinação e aumenta a eficiência do processo de oxidação dos compostos orgânicos / Abstract: Porous films electrodes containing TiO2 and WO3 were deposited on SnO2:F (FTO) conducting glass from aqueous suspensions with TiO2 Degussa P25®, WO3 precursors and polyethylene glycol, followed by heating (450°C, 30 min). The maximum absorption was respectively observed at 390 and 480 nm for TiO2 and WO3 samples; intermediate values were obtained for the mixtures. The TiO2 films, ca. 4.5 mm, consisted of interconnected spherical particles (25 nm), resulting in a porous surface and excellent substrate coverage. Adding H2WO4 on the TiO2 suspension resulted in the TiO2/WO3 film, with comparable morphology but less porous. The WO3 electrode exhibited a non-uniform surface coverage with disk shaped particles (0.1-1mm). The morphology of the bilayer WO3-TiO2, obtained from the deposition of a TiO2 film on the top of a WO3 electrode, was similar to that observed for TiO2. The electrochemical properties were investigated in Na2SO4 aqueous solution, in the dark and under polychromatic irradiation. The electrodes exhibited an n-type semiconductor behavior, with negative photopotential and anodic photocurrent; higher photocurrent was observed for electrodes containing WO3. The electrodes were used for remediation of Rhodamine 6G dye aqueous solution (10 mmol L) using the configurations for heterogeneous photocatalysis (HP) and electro assisted-HP by polarization at 0.7 V (EHP). Under irradiation, at the initial 3 h, a pseudo first order kinetics was observed for the dye solution bleaching; in HP configuration, the WO3, TiO2 and WO3-TiO2 electrodes promoted respectively 8, 34 and 38 % of dye removal (apparent rate constants of 0.37x10; 2.3x10 and 2.8x10 min) and, without photocatalysts, only 4 %. Higher efficiency was observed under EHP configuration; for WO3-TiO2, 44 % of dye was removed (3.2x10 min). Also, the electrodes were used for treatment of aqueous solution containing the 17 a-ethynylestradiol hormone (34 mmol L); after 4 h in HP and EHP configurations, the remediation with TiO2 resulted in degradation of 38 and 48 % of the hormone, and the TiO2/WO3 electrode promoted 45 and 54 %. HP and EHP configuration resulted in similar mineralization for both electrodes, 15 and 19 %, respectively; without the photocatalyst, 10 % of degradation was observed (4 % of mineralization). The dye and hormone photocatalytic oxidation by these electrodes was discussed considering energy diagrams; for the electrodes containing WO3, the better harvesting of visible radiation, as well as, the favorable relative position of valence and conduction band of these semiconductors, promotes the separation of photogenerated charges, which minimizes their recombination, improving the efficiency of organic compounds oxidation / Doutorado / Físico-Química / Doutor em Ciências

This thesis studies properties of hydrogel, which arises on the basis of electrostatic and hydrophobic interactions between hyaluronan chain and micelles of cationic surfactant. A native sodium hyaluronan at molecular weight 750–1 000 kDa and a cationic surfactant CTAB (cetyltrimethylammonium bromide) were used. This hydrogel was assessed as a material for drug delivery systems. The hydrogels were made by mixing 200mM CTAB with 0.5% hyaluronan, both dissolved in 0.15M aqueous solution of NaCl simulating physiological solution. Methods used in this study were steady-state and time-resolved fluorescence spectroscopy, more accurately time-resolved emission spectra (TRES) and deconvolution of steady-state emission spectra of a whole sample by means of parameters gained from fluorescence intensity decays at a set of wavelenghts. Selected systems were investigated by three fluorescent probes, prodan, laurdan and rhodamine 6G. The first two mentioned probes were in hydrogel localized only within micelles in three different microenvironments. Rhodamine 6G pointed out that in hydrogel the aqueous environment is significantly restricted in comparison to purely micellar solution. In addition, rhodamine informed about less available micelle surfaces, caused by hyaluronan chains occupation. There were no interactions between the probes and hyaluronan chains. Freshly made hydrogels showed almost the same results as after a week of maturation under its supernatant.

In this diploma thesis were investigated in terms of microviscosity liquid and condensed systems composed of hyaluronan (Hya) and cationic surfactant cetyltrimethylammonium bromide (CTAB). The excitation and emission spectra, lifetime, steady-state fluorescence anisotropy and time-resolved fluorescence anisotropy of the samples were measured. First, was studied the formation of hydrophobic domains in the system Hya-CTAB at concentration of CTAB lower than its critical micelle concentration in an aqueous solution and 0.15M NaCl. It was found that in an aqueous solution small hydrophobic domains linked to chains Hya are formed. Then an increasing concentration of CTAB leads to phase separation and formation of gel. Due to the addition of NaCl then leads to the reorganization of this system and probably the formation of free micelles in the solution. Were also studied condensed phase of system Hya-CTAB-NaCl at high concentrations of surfactant during fourteen days of ageing. It was found that the microviscosity of hydrophobic domains is constant, but the microviscosity of hydrophilic parts gradually decreases.