[diss] Sähkötekniikan korkeakoulu / ELEC

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    Connectivity for smart grids: Novel communications solutions in evolving electrical grids
    (Aalto University, 2024) Borenius, Seppo; Lehtonen, Matti, Prof., Aalto University, Department of Electrical Engineering and Automation, Finland; Costa Requena, Jose, Dr., Aalto University, Department of Information and Communications Engineering, Finland; Informaatio- ja tietoliikennetekniikan laitos; Department of Information and Communications Engineering; Sähkötekniikan korkeakoulu; School of Electrical Engineering; Mähönen, Petri, Prof., Aalto University, Department of Information and Communications Engineering, Finland
    Increasing electrification and power grid evolution to allow integrating large amounts of renewable generation will be key enablers for creating a sustainable, carbon-neutral energy system. The expected increased demand for electricity will result from efforts to reduce the use of fossil fuels in the industry, heating, and transport sectors. The larger share of intermittent generation from renewable sources, such as wind and solar, as well as the decreasing number of traditional controllable inertia-providing generators will lead to higher system volatility. This volatility challenge is worsened by the lack of seasonal system-level electric energy storage capacity. In distribution grids, the volatility challenge and increased power system dynamics will necessitate expanded automation, which in turn will require enhanced connectivity solutions. This thesis contributes first by taking a forward-looking, system-level view in exploring possible power grid futures and then by identifying approaches for integrating electric power grids with Information and Communications Technologies (ICT) in these futures. The overall research problem of the thesis is defined as follows: How can communications solutions support the creation of sustainable resilient power grids by the 2030s? The research extensively utilises expert panels, formal scenario planning and value networks based on the Finnish power grid context as a case example. The thesis proceeds in three stages. The thesis first establishes multiple scenarios, i.e. possible power grid futures. These describe the potential evolution from the perspective of grid management and the services offered to customers. Thereafter, in the second stage, the thesis explores the role of both the latest as well as anticipated new communication technologies, the feasibility of applying these in future distribution grids, and the potential impact of softwarisation on power grid architectures. The more extensive use of ICT gives rise to new attack points for malicious actors and consequently increases the vulnerability of the electric energy system. The thesis continues by identifying the most significant cybersecurity risks and trends, followed by an examination of how well these risks and trends are currently analysed and understood in academia and industry. In the third stage, the thesis shifts the focus to the business level. The opportunities for various actors are explored by identifying the potential industry (business) architectures for the communications solutions required to manage future distribution grids. The results of this thesis should help stakeholders, such as actors within the energy and ICT sectors as well as regulators and politicians, to consider alternative futures in order to make correct decisions on which businesses to be in, how to invest until the 2030s, as well as how to ensure the reliability and cost efficiency of the electric power system.
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    Advanced Earth Fault Mitigation Using Virtual Air Gap Reactors
    (Aalto University, 2024) Sevsek, David; Lehtonen, Matti, Prof., Aalto University, Department of Electrical Engineering and Automation, Finland; Sähkötekniikan ja automaation laitos; Department of Electrical Engineering and Automation; Power Systems and High Voltage Engineering; Sähkötekniikan korkeakoulu; School of Electrical Engineering; Lehtonen, Matti, Prof., Aalto University, Department of Electrical Engineering and Automation, Finland
    The shift towards electrification of energy sectors and global climate change has increased the demand for reliable and safe electricity networks. This has posed a significant challenge for distribution system operators (DSOs), especially when dealing with single-line-to-earth (SLTE) faults, the most common type of faults in distribution networks. Traditional arc suppression coils (ASCs) used to limit SLTE fault currents are often limited by operational constraints. A novel type of ASC, the virtual air gap (VAG) reactor, may help to overcome this issue. These reactors use a set of auxiliary coils controlled by power electronics that can change their inductance within milliseconds. This quick inductance-changing capability could make VAG reactors a valuable asset when used as ASCs in compensated networks. To investigate the potential of VAG reactors, a dynamic time-domain model of VAG reactors was developed and validated by comparing it with a low-voltage (LV) VAG reactor. Based on the dynamic model, two distinct control approaches for VAG reactors were developed with the objective of using the reactor as an ASC in a compensated medium voltage (MV) distribution network. One controller has active harmonic mitigation, while the other requires less power but cannot control harmonics. The combination of the dynamic VAG reactor model along with the two distinct controllers was then compared to a traditional ASC in a series of time-domain MATLAB/Simulink simulations of a compensated MV distribution network. Furthermore, a series of laboratory tests were conducted to investigate the duration of an arc before its self-extinction, depending on the magnitude of the arcing current, the rate of rise of transient recovery voltage (RRTRV), and the length of the initial spark gap. The results of the simulations showed that the residual fault current can be effectively reduced during a SLTE fault by changing the inductance of the reactor to its optimal operating point. Both control approaches demonstrated the typical features of traditional ASCs, including the slowly increasing recovery voltage after fault extinction. The laboratory arc test showed that the duration of an arc before self-extinction depends more on the RRTRV than on the magnitude of the arcing current for currents at 10 A or below. Furthermore, it was found that smaller spark gaps result in longer burning arcs due to their more stable characteristics. The combination of the results of the laboratory arc test with the simulation results of the VAG reactors in the network simulation led to the conclusion that VAG reactors can be a viable alternative to traditional ASCs and help enhance the reliability of electricity networks.
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    Reducing optical and electrical losses in germanium via nanostructures and surface passivation
    (Aalto University, 2024) Isometsä, Joonas; Vähänissi, Ville, Dr., Aalto University, Department of Electronics and Nanoengineering, Finland; Elektroniikan ja nanotekniikan laitos; Department of Electronics and Nanoengineering; Electron Physics Group; Sähkötekniikan korkeakoulu; School of Electrical Engineering; Savin, Hele, Prof., Aalto University, Department of Electronics and Nanoengineering, Finland
    Germanium (Ge) offers several distinct advantages over silicon, including higher carrier mobility and narrower bandgap, making it an attractive substrate material for various optoelectronic ap-plications, such as near-infrared detectors, multijunction solar cells, and thermophotovoltaics. However, the full potential of Ge has not been realized yet due to challenges related to optical and electrical losses, namely high reflectivity and high recombination at the surfaces. First, this dissertation addresses the high reflectivity of Ge surfaces by developing nanostructures, which could enable minimal reflectance over a wide spectral range resulting in visibly pitch-black Ge (b-Ge). b-Ge processes for two different fabrication methods, inductively-coupled plasma reactive-ion etching (ICP-RIE) and metal-assisted chemical etching (MACE), are developed. ICP-RIE is shown to be capable of producing b-Ge with a reflectance below 1% across 400–1600 nm wavelength range, whereas the MACE b-Ge reflectance remains somewhat higher at an average of 9%. Nevertheless, the MACE process provides some advantages over ICP-RIE, such as being con-siderably lower cost, making it equally competitive. In order to address the second main challenge, i.e. the high surface recombination, an ALD Al2O3-based surface passivation process is developed. ALD Al2O3 is demonstrated to provide efficient pas-sivation for polished Ge surfaces, achieving a surface recombination velocity (SRV) of 6.55 cm/s. This is obtained with optimized process parameters such as an HCl pre-treatment and a post-anneal in 400 °C for 30 mins. After more detailed characterization, it is identified that the low SRV is based on a strong field-effect rather than good chemical passivation. In order to improve the che-mical passivation, an ultra-high vacuum anneal as an ALD pre-treatment is employed. Conse-quently, the chemical passivation is improved but as a trade-off, the field-effect is reduced leading to a similar level of overall passivation. Finally, the above results are combined targeting a simultaneous reduction of reflective and recombination losses. In the case of ICP-RIE fabricated b-Ge, some chemical residues are obser-ved to deteriorate the surface passivation. Cyclical HCl and H2O2-based cleaning process is seen to remove the residues but simultaneously leads to changes in surface morphology and reflectance. Hence a trade-off between reflectance and surface passivation is necessary. As an example, without deteriorating the reflectance too much (< 2%), an SRV of 30 cm/s is obtained. In the case of MACE, achieving efficient surface passivation seems to be more complicated. The obtained results in this thesis give a good basis for designing high-efficiency optoelectronic devices.
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    Analysing flexibility in energy system investment planning - Impact of variable renewable energy, temporal structures and operational constraints
    (Aalto University, 2024) Helistö, Niina; Kiviluoma, Juha, Dr., VTT Technical Research Centre of Finland, Finland; Sähkötekniikan ja automaation laitos; Department of Electrical Engineering and Automation; Power Systems and High Voltage Engineering; Sähkötekniikan korkeakoulu; School of Electrical Engineering; Lehtonen, Matti, Prof., Aalto University, Department of Electrical Engineering and Automation, Finland
    The proliferation of wind and solar energy increases the flexibility needs of power systems on multiple temporal and spatial scales. While various technologies exist and are being developed that can provide flexibility, exploring the interactions and roles of new and existing technologies in flexibility provision requires investment planning models which can correctly capture temporal, spatial, sectoral and technological diversity, and detail. Being aware of the most important details and the state-of-the-art methods for modelling them will facilitate higher quality planning results and help avoid misguided investment decisions. This dissertation focuses on developing and exploring methods and frameworks for assessing the need for and provision of flexibility when planning energy system investments. The methods should be able to capture important temporal variations, as well as the necessary operational constraints of energy systems. In addition, a number of case studies were carried out to explore the sensitivity of electricity prices, the role of conventional thermal power plants and the benefits of different energy technologies in future energy systems. The case studies provide insight into the type of power system flexibility needed with increasing shares of wind and solar energy, as well as insight into further modelling needs. The temporal representation of the investment planning model is shown to significantly impact the total system costs resulting from the planning outcome. Correctly capturing extreme periods and interannual variations in weather are key to enhancing resource adequacy considerations. Similarly, intra-annual variations need to be captured using, for example, appropriately selected representative days or weeks. According to the results, the best selection method and the sufficient number of selected periods depend on system characteristics. The results also suggest that the modelling of power plant start-ups and shutdowns, ramp rates, as well as simplified stability requirements and reserve products generally has less impact on total costs than the various possible temporal representations. However, correctly capturing the flexibility of sector-coupling technologies is demonstrated to have a significant impact. Investment planning capabilities and additional features related to flexibility were included in Backbone, an adaptable energy system modelling framework, which is also available as opensource software. Backbone can be utilised to create models for studying the design and operation of high-level large-scale and fully detailed smaller-scale energy systems from various perspectives.
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    Development of piezoelectric microelectromechanical systems for multiaxial motion and sensing
    (Aalto University, 2024) Bespalova, Kristina; Ross, Glenn, Dr., Aalto University, Department of Electrical Engineering and Automation, Finland; Sähkötekniikan ja automaation laitos; Department of Electrical Engineering and Automation; Electronics Integration and Reliability; Sähkötekniikan korkeakoulu; School of Electrical Engineering; Paulasto-Kröckel, Mervi, Prof., Aalto University, Department of Electrical Engineering and Automation, Finland
    Piezoelectric materials offer several advantages for MEMS applications due to their superior direct electromechanical coupling and low voltage consumption, especially when compared to electrostatic-based MEMS. Integrating piezoelectric thin films in MEMS also allows for a significantly smaller chip footprint than devices employing other transduction techniques. Furthermore, thin piezoelectric films can be integrated into the fabrication of multifunctional devices capable of three-dimensional motion (3D motion). Such 3D piezoMEMS enable driving and sensing along the x, y, or z-axes using components of a single element. This distinguishes 3D piezoMEMS from conventional MEMS that utilize elements that often facilitate motion in only one direction. This dissertation investigates the development of a new fabrication approach and adapting and optimizing existing fabrication techniques for 3D piezoMEMS fabrication. Pure lateral motion of a single MEMS element is implemented by placing metal organic chemical vapour deposited aluminium nitride (MOCVD AlN) thin films on the vertical surfaces of the Si cantilever. The fabrication approach demonstrated in the work unlocks the piezoelectric and electrode material deposition potential on vertical sidewall structures in the fabrication of advanced 3D piezoMEMS.
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    Diffusion-Driven Charge Transport in III–V Optoelectronic Devices
    (Aalto University, 2024) Myllynen, Antti; Oksanen, Jani, Dr., Aalto University, Department of Neuroscience and Biomedical Engineering, Finland; Elektroniikan ja nanotekniikan laitos; Department of Electronics and Nanoengineering; Sähkötekniikan korkeakoulu; School of Electrical Engineering; Sopanen, Markku, Prof., Aalto University, Department of Electronics and Nanoengineering, Finland; Ilmoniemi, Risto, Prof., Aalto University, Department of Neuroscience and Biomedical Engineering, Finland
    Optoelectronics that seamlessly convert electrical energy to optical energy and vice versa have irreversibly changed our everyday lives through, e.g., the ubiquitous light-emitting diodes (LEDs) and increasingly important solar cells. The LEDs have revolutionized the lighting industry with improved efficiency and are also used to illuminate virtually every modern display, from smartphones and laptops to televisions. In parallel, solar cells generate increasing amounts of renewable energy, a critical component for global environmental initiatives. Despite recent advances in LEDs and solar cells, their core design principle has remained static: the active region (AR), where energy conversion mainly occurs, is placed between n- and p-doped high bandgap materials. However, emerging and more demanding solid-state fields have begun to expose limitations inherent to this core design. These limitations mainly comprise (1) resistive losses and (2) current crowding that can strongly increase heat generation at high powers, as well as (3) contact shading, which can notably reduce the illumination of solar cells. This thesis explores the possibilities of diffusion-driven charge transport (DDCT) within III–V compound semiconductor optoelectronics. In contrast to conventional LEDs and solar cells, the AR of the DDCT devices does not have to be placed between the n- and p-doped materials, as the AR can be excited via diffusion currents. This design allows near-surface active regions and opens the door for using III–V materials to fabricate interdigitated back-contact (IBC) structures that have historically been possible only for state-of-the-art silicon solar cells. The primary objectives of this thesis are to explore the general requirements, limits, and possible advantages of the DDCT devices through drift-diffusion simulations and to develop a fabrication process to demonstrate these unconventional laterally-doped gallium arsenide (GaAs) based structures also in practice. The simulation results suggest that the proposed DDCT structure can allow efficient and nearly resistance-free LEDs with fully exposed front surfaces for optimizing light extraction. Similarly, the results show that the structure is reciprocal and allows IBC designs for solar cells, which are also suitable for concentration photovoltaics. As such, DDCT devices promise to eliminate contact shading and mitigate current crowding challenges in GaAs-based LEDs and solar cells. To demonstrate the viability of these devices in practice, a method for fabricating them using selective area diffusion doping was developed. The first generation of DDCT prototypes was successfully demonstrated using thermal annealing to selectively redistribute dopant atoms incorporated in the device structure. These devices exhibited promising current-voltage and optical characteristics, suggesting that the developed annealing process holds great potential for fabricating DDCT devices.
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    Planning of Wireless Networks for 5G/6G Applications
    (Aalto University, 2024) Abedi, Mohsen; Dowhuszko, Alexis Alfredo, Dr., Aalto university, Department of Information and Communications Engineering, Finland; Informaatio- ja tietoliikennetekniikan laitos; Department of Information and Communications Engineering; Risto Wichman Group; Sähkötekniikan korkeakoulu; School of Electrical Engineering; Wichman, Risto, Prof., Aalto university, Department of Information and Communications Engineering, Finland
    The rise of 6G will allow wireless communication networks to achieve unprecedented levels of connectivity, capacity, and coverage. As part of 6G, higher frequency bands such as mmWaves, Terahertz, and visible light can be utilized to provide larger capacity than sub-6 GHz b ands currently used in 4G/5G. However, as frequencies increase, the signal range and obstructions may limit the signal's coverage, creating a significant challenge when it comes to ensuring seamless coverage. Wireless network planning aims to determine the minimum number of wireless access points and their locations in the service areas. Planning is key to achieving seamless coverage, optimizing bandwidth utilization, reducing energy consumption, and ensuring sufficient quality of services. Planning is an NP-hard problem that requires an exhaustive search in order to reach the optimal solution. Due to the large dimensions, parameters, and diverse requirements of networks, it isimpossible to conduct an exhaustive search for network planning. It can, however, be made feasible by developing mathematical tools and optimization models. The purpose of this dissertation is to examine the issue of wireless network planning in light of the different wireless network requirements. Based on Voronoi diagrams and Delaunay triangulation, a regularity algorithm is proposed for planning wireless cellular networks that maximize coverage and balance cell loads outdoors. In addition, we propose a graph that models the indoor areas taking into account the propagation limits imposed by signals at higher frequencies. We then demonstrate that the deployment of access points for seamless Line-of-Sight coverage of indoor areas can be achieved by partitioning this graph into cliques, each representing a wireless access point. As a final step, we use this graph modeling to analyze network requirements to ensure that access points are deployed in a fashion that meets various operational requirements, for example, Line-of-Sight backhauling between access points and multiple Line-of-Sight coverage for positioning.
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    Attention-based End-to-End Models in Language Technology
    (Aalto University, 2024) Rouhe, Aku; Grósz, Tamás, Dr., Aalto University, Speech Recognition, Finland; Informaatio- ja tietoliikennetekniikan laitos; Department of Information and Communications Engineering; Speech Recognition Research Group; Sähkötekniikan korkeakoulu; School of Electrical Engineering; Kurimo, Mikko, Prof., Aalto University, Department of Information and Communications Engineering, Finland
    Speech recognition specifically, and language technology more generally, have started to find everyday use. Challenging language tasks have become feasible through a continued growth in data resources and compute capacity, and through neural networks methods which are able to take advantage of this growth. As applications continue to integrate more deeply into our lives, it is important to understand and follow the many directions that these fields may take. At the turn of the 2020-decade, end-to-end models have received a lot of attention. End-to-end models hold  promise of simpler solutions, which nonetheless may scale better with data and compute. On the other hand, end-to-end models defy decomposing tasks into easier subproblems. This decomposition allows modular designs, which permit a wider variety of data sources to be used. It remains unclear whether the end-to-end models are truly an improvement over previous technologies. It is not straight-forward to compare end-to-end and decomposed solutions fairly, because of their many differences. This thesis proposes a principled approach for comparisons of such heterogeneous solutions and applies it to speech recognition. In their default configuration, the end-to-end models forego many useful data sources, and rely solely on expensive end-to-end labeled data. This thesis explores methods for leveraging additional data sources in speech recognition, canonical morpheme segmentation, and spoken language translation. Additional data sources are especially useful in low data and under-resourced tasks. These difficult tasks often need the structure imposed by decomposed solutions. This thesis investigates end-to-end models in an under-resourced speech recognition and a low data canonical morpheme segmentation task. The tasks explored in this thesis are connected through a shared architecture: attention-based encoder-decoder models. Though these attention-based models are most often outperformed by hidden Markov model speech recognition systems, they showcase remarkable flexibility. They succeed in speech recognition using just tens of hours and upto thousands of hours of data. They learn to exploit auxiliary speaker and segmentation-marker inputs. They perform spoken language translation in one step. They even yield the author a first place in a public benchmark competition.
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    Plasma-enhanced atomic layer deposition of aluminum nitride : characteristics and applications
    (Aalto University, 2024) Seppänen, Heli; Suihkonen, Sami, Dr., Aalto University, Department of Electronics and Nanoengineering, Finland; Kauppinen, Christoffer, Dr., VTT Technical Research Centre of Finland Ltd., Finland; Elektroniikan ja nanotekniikan laitos; Department of Electronics and Nanoengineering; Nanoscience and Advanced Materials; Sähkötekniikan korkeakoulu; School of Electrical Engineering; Lipsanen, Harri, Prof., Aalto University, Department of Electronics and Nanoengineering, Finland
    Plasma-enhanced atomic layer deposition (PEALD) offers a variety of advantages over other thin film growth techniques, such as conformal coverage of complex surface structures. However, low crystallinity has been a drawback for PEALD aluminum nitride (AlN) thin films, which makes it impossible to use in many applications. In this thesis, a process for reaching a higher quality AlN grown with PEALD was studied. The process included an added plasma step into the PEALD cycle, atomic layer annealing (ALA). The results of this thesis are divided into material characteristics of the improved PEALD ALA AlN and use of PEALD ALA AlN and PEALD AlN thin films in diverse applications. AlN grown with the PEALD ALA process has improved stoichiometry, crystallinity, and c-axis orientation, and contained less carbon and hydrogen impurities. Amount of oxygen impurities has increased. Post deposition annealing at high temperature in vacuum reduced impurities but did not improve the crystallinity further. The substrate also has an impact on the obtained crystal quality of the film and could aid the AlN film to achieve the preferred structure. The ALA AlN was measured to be piezoelectric when deposited on an aluminum substrate. In addition, ALA AlN grows crystalline on vertical sidewalls. The use of PEALD ALA AlN as a transition layer for further metalorganic chemical vapor deposition regrowth was demonstrated successfully. Silicon surface passivation was demonstrated with PEALD AlN. The film provides passivation for the surface and the highest carrier lifetime was obtained with higher deposition temperature and a combination of annealing and firing as a postdeposition heat treatment.
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    Network Slice Mobility and Service Function Chain Migration across Multiple Administrative Cloud Domains
    (Aalto University, 2024) Addad, Rami Akrem; Dutra, Diego Leonel Cadette, Prof., Federal University of Rio de Janeiro, Brazil; Tietoliikenne- ja tietoverkkotekniikan laitos; Department of Communications and Networking; Sähkötekniikan korkeakoulu; School of Electrical Engineering; Manner, Jukka, Prof., Aalto University, Department of Information and Communications Engineering, Finland
    The maturing 5G network technology sees growing commercial deployments, with a shifting focus to service delivery. 5G networks, a common platform for diverse services, utilize network slicing for service isolation. Cloud-native services, composed of interdependent micro-services, are allocated to network slices spanning multiple areas, domains, and data centers. Due to mobility events caused by mobile end-users, slices with their assigned resources and services need to be re-scoped and re-provisioned. This requires slice mobility, which involves a slice moving between service areas. Slice mobility requires the inter-dependent service and resources to be migrated to reduce system overhead and to ensure low-communication latency by following end-user mobility patterns. Recent advances in computational hardware, Artificial Intelligence, and Machine Learning have attracted interest within the communication community, with increased research interest in self-managed network slices. However, migrating a service instance of a slice remains an open and challenging process given the needed coordination between inter-cloud resources, the dynamics, and the constraints of inter-data center networks. In this regard, this dissertation defines and enables smooth network slicing mobility patterns while maintaining both system and network resources stable. Specifically, we design, implement, and evaluate our proposed migration framework. Then, we design and define different network slice mobility patterns with their corresponding grouping methods and relevant mobility triggers. Next, we introduce various SFC migration strategies as an underlay technology enabler for network slice mobility patterns. After that, we propose an agent for automating the triggers selection process for enabling various network slice mobility patterns. Finally, we develop a network-aware agent capable of selecting accurate bandwidth values while ensuring fast and reliable service migration, thus enabling slice mobility while matching network and system requirements. In each section of this dissertation, the research results are evaluated and validated under different configurations in real-world settings or simulated environments. This dissertation provides recommendations for improving and extending the notion of mobility in network slices while also highlighting the various outstanding questions and suggesting future challenges and research directions.
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    Probabilistic Cache Policy Design for Cellular Networks with Stochastic Geometry Analysis
    (Aalto University, 2023) Amidzade, Mohsen; Al-Tous, Hanan, Dr., Aalto University, Finland; Informaatio- ja tietoliikennetekniikan laitos; Department of Information and Communications Engineering; Sähkötekniikan korkeakoulu; School of Electrical Engineering; Tirkkonen, Olav, Prof., Aalto University, Department of Information and Communications Engineering, Finland
    The annual data traffic of mobile cellular networks is growing explosively, which has led to backhaul link congestion and latency during data reception from cellular networks. For the fifth generation (5G) of cellular systems, faster transmission speeds, lower latency, and higher spectral efficiency than the previous generations are required. Edge caching promisingly fulfills these requirements by alleviating the unprecedented data congestion and traffic escalation issues of cellular networks. Edge caching is a technique to proactively store the potentially preferable files at the edge of the network (e.g. base stations or user equipment). To achieve an appropriate cache strategy, the two phases of cache placement and cache delivery need to be addressed and optimized. Moreover, a cache policy can be designed based on a static or dynamic framework. For the former, only one shot of network operation is considered, while for the latter, the dynamics of network operation are taken into account. This thesis aims to design optimal static and dynamic caching policies based on the considered model of network operation. For the static caching, this thesis considers the multipoint multicast transmission scheme with a probabilistic cache placement. Building on stochastic geometry, the outage probability is analyzed as network performance to design a static cache strategy. As such, a constrained optimization problem is formulated considering resource and cache allocation parameters, and two algorithms are devised to numerically solve it. Simulation results show that the usage of multipoint multicast is a promising and competitive approach compared to the singlepoint scheme from the literature. This thesis also proposes a hybrid scheme combining the multiantenna single-point unicast and multipoint multicast components to simultaneously leverage the advantages of these schemes for a static cache strategy. To find the hybrid cache solution, a timevarying optimization problem is formulated considering cache and resource allocation parameters as well as content assignment between those two different components. Simulation results indicate the superiority of the proposed hybrid scheme from the spectral efficiency perspective. For the dynamic caching, the dynamics of the user requests in a cellular network are formulated based on a Markov decision process. As such, a reinforcement learning algorithm is exploited to devise a dynamic cache strategy. Simulation results show significant improvements brought by proposed dynamic caching from the quality-of-service and power consumption point-of-view.
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    Multi-band 5G Antenna Designs for Smartphones
    (Aalto University, 2024) Chen, Quangang; Lehtovuori, Anu, Dr., Aalto University, Department of Electronics and Nanoengineering, Finland; Ala-Laurinaho, Juha, Dr., Aalto University, Department of Electronics and Nanoengineering, Finland; Elektroniikan ja nanotekniikan laitos; Department of Electronics and Nanoengineering; Sähkötekniikan korkeakoulu; School of Electrical Engineering; Viikari, Ville, Prof., Aalto University, Department of Electronics and Nanoengineering, Finland
    In the pursuit of increasing data transmission rates, mobile communications have rapidly evolved into the 5G era. With more and more frequency bands being specified and utilized, one of the longstanding challenges in mobile phone antenna design has been to cover multiple communication bands within the limited internal space of a phone. The introduction of Multiple-Input Multiple-Output (MIMO) technology and millimeter-wave (mm-wave) technology, together with the attractive visual appearance of handsets, has presented new challenges for mobile phone antenna design. The first part of this thesis concentrates on frequency-reconfigurable antennas, specifically utilizing lumped components. A full metal-rimmed model serves as a basis in the antenna designs covering hepta-band of 4G and C-band of 5G. A decoupling method of 5G MIMO antennas is also proposed based on the current suppression in a ring slot. Subsequent designs in this part focus on the frequency-reconfigurable antennas in the mm-wave frequency band. Required capacitance is first studied in the frequency band from 24 to 43.5 GHz, and practical antenna design is then implemented with commercially available tunable components, covering a frequency band from 23.2-30.2 GHz with total efficiency larger than -2.5 dB. A novel cluster array concept is introduced in the second part for frequency tunability through the adjustment of feeding weights. Realized gains of antenna arrays are maximized using eigenvalues of electric-field results. The proposed approach can be applied to various antenna designs to improve the spherical coverage in a wide frequency range. For instance, diverse patch and dipole elements, which can be seen as multiple-resonance circuits, are employed to illustrate this concept. The third part presents a dual-polarized end-fire antenna array as a supplement to broadside antennas achieving full spherical coverage required for the 5G mm-wave applications. Multiple resonant modes are generated through the use of a novel stacked antenna with a low profile for vertical polarization. The overlapped bandwidth of the vertical polarization and horizontal polarization ranges from 24 to 43.5 GHz. The methods developed in this thesis achieve the multiple frequency bands for 5G mobile communications. This work contributes to the antenna designs for modern smartphones, incorporating the research between practical applicability and innovative approaches.
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    Engineering the Optical Properties of Semiconducting Two-Dimensional Materials
    (Aalto University, 2024) Turunen, Mikko; Pekola, Jukka, Prof., Aalto University, Department of Applied Physics, Finland; Elektroniikan ja nanotekniikan laitos; Department of Electronics and Nanoengineering; Photonics; Sähkötekniikan korkeakoulu; School of Electrical Engineering; Sun, Zhipei, Prof., Aalto University, Department of Electronics and Nanoengineering, Finland
    Over the last two decades, two-dimensional (2D) materials have emerged as a promising platform for photonic and optoelectronic applications. Especially, transition metal dichalcogenides (TMDs) have gained huge attention due to their exceptional properties, including strong photoluminescence, strong spin–orbit coupling, high optical non-linearity and unique valley physics. Combining these properties with the atomical thickness and tuneable band gap makes TMDs an attractive platform for various applications. Furthermore, TMD-based single photon emitters (SPEs) are of special significance for quantum photonic technologies. However, addressing the coherence limitations of the SPEs in TMDs has remained elusive, necessitating a deeper understanding of them. This doctoral thesis explores methods to engineer the optical properties of 2D TMDs using optical modification and atomic layer deposition (ALD). The optical modification involves femtosecond pulsed light illumination of monolayer TMDs in an inert environment, resulting in altered physical and optical properties. ALD of TiO2 on 2D TMDs induces intensity reduction and spectral shifts in their photoluminescence (PL) and Raman responses, and increased exciton state lifetimes. The effects arise from chemical interactions, dielectric screening, and mechanical strain. Notably, the chemical effects, such as doping and oxidation, could be significantly mitigated by depositing a protective hBN layer on top of TMDs. The results presented here shed light on the physical properties of 2D TMDs and their potential for diverse applications (e.g., single photon emission). This thesis contributes essential knowledge to the rapidly developing field of 2D materials and quantum photonic research, serving as a foundation for future investigations and advancements.
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    IoT and DLT Integration—A Choice of Tradeoffs?
    (Aalto University, 2023) Paavolainen, Santeri; Nikander, Pekka, Dr., Finland; Sahlin, Bengt, Dr., Ericsson, Finland; Informaatio- ja tietoliikennetekniikan laitos; Department of Information and Communications Engineering; Sähkötekniikan korkeakoulu; School of Electrical Engineering; Manner, Jukka, Prof., Aalto University, Dept. Information and Communications Engineering, Finland
    The integration between Internet of Things (IoT) systems and Distributed Ledger Technologies (DLTs) seems to offer a possibility to address some of the shortcomings often encountered in the widespread deployment of IoT systems, as well as open a potential for novel business models. Existing research on IoT-DLT integration has, however, focused primarily on addressing functional problems on a high level and leaving many of the operational problems occurring in a real-world scenario out of scope. For example, a Raspberry Pi single board computer is often used as an analogue for an IoT device—even when it costs ten or hundred times more than an embedded processor inside a low-cost IoT device. Crucially, the cost of an IoT device is a major factor in the economic feasibility at industrial scale. This cost pressure implies that most IoT devices will be relatively cheap and as a consequence have only a meager amount of computing power, memory capacity, and network bandwidth, commonly referred to as constrained devices. Thus, it is important to consider not only macroscopic use cases, but to also address challenges low-cost and constrained devices face if we really want to enable DLT connectivity on a typical IoT device.  This dissertation describes different integration approaches used for IoT-DLT systems, and qualifies their applicability for constrained devices. Of particular importance is an integration method based on light protocols, which provide an enticing tradeoff of providing relatively high security while requiring substantially less resources as operating as a normal, fully functional peer on the DLT. Yet, some of these security tradeoffs can be shown to be worse than commonly assumed, leading to IoT devices being vulnerable to state injection attacks. This work proposes two new novel solutions to address such attacks: decentralised beacons and subset nodes. Decentralised beacons leverages on the existence of a trusted third party in IoT systems—the device owner—to provide scalable attestations of the DLT ground state to a low-power device, with a tradeoff of increased latency to DLT state changes. Subset nodes, in turn, addresses the latency issue by recognizing that most IoT applications will observe only a small subset of the whole DLT state, and by restricting its view to only this subset state, a higher level of security assurances can be reached with modest computing and storage requirement increases. These two methods are complementary and can be deployed separately or in combination.
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    Material characterization, modeling, and incorporation of the models in the machine simulation of large-diameter synchronous machines
    (Aalto University, 2023) Gürbüz, Ismet Tuna; Martin, Floran, Dr., Aalto University, Department of Electrical Engineering and Automation, Finland; Aydin, Ugur, Dr., ABB Oy, Finland; Sähkötekniikan ja automaation laitos; Department of Electrical Engineering and Automation; Sähkötekniikan korkeakoulu; School of Electrical Engineering; Belahcen, Anouar, Prof., Aalto University, Department of Electrical Engineering and Automation, Finland
    This dissertation presents a comprehensive methodology for the realistic and computationally efficient simulation of large-diameter synchronous machines accounting for the effect of cutting on iron losses and magnetization. To achieve this, magnetic materials used in the machine parts are experimentally characterized, material models based on the characterization are developed, the developed models are incorporated into finite-element (FE) simulation software, and machine simulation is performed with the incorporated models. Non-oriented punched electrical steel sheets used in the stator laminations are studied experimentally under different uniaxial stress conditions using a modified single-sheet tester. It is shown that the effect of stress on the iron losses of the punched samples differs based on the extent of degradation observed in the samples following the cutting procedure. Subsequently, in the material modeling, the focus is given to the modeling of punching. A continuous material modeling approach with an exponential deterioration profile is used for the magnetization, and iron losses are modeled similarly by modifying the coefficients of Jordan's method. Thick laser-cut steel laminations used in the rotor poles are studied experimentally using a ringcore measurement system. The characterization of the material properties and iron losses is then achieved by a 2-D axisymmetric FE modeling of the lamination cross-section with the inclusion of a continuous local material model using a quadratic deterioration profile. It is shown that the inclusion of the edge effects for the thick laminations is needed, which requires a 2-D modeling. In light of this, a simple 2-D analytical model is developed for eddy-current loss computation. To achieve a computationally efficient and accurate implementation of cutting deterioration into electromagnetic FE simulation, a new methodology for numerical integration is proposed. The validity of this approach is confirmed by comparing it to the analytical solution for a 2-D beam geometry. Subsequently, the method is utilized in the 2-D FE simulation of transformers, resulting in an enhanced computational efficiency when compared to existing methods. Time-stepping simulation of the studied large-diameter synchronous machine is achieved with the incorporated models developed for the stator laminations and rotor poles following the proposed methodology. The effect of cutting on the loss components and machine operating points is analyzed. The results demonstrate that accurate incorporation of the cutting effect in the machine simulation increases the machine's losses by 16.4 kW, necessitating improved cooling capabilities.
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    Harnessing the physical properties of objects for robotic grasping and manipulation
    (Aalto University, 2023) Nguyen Le, Tran; Abu-Dakka, Fares J., Prof., Mondragon University, Spain; Sähkötekniikan ja automaation laitos; Department of Electrical Engineering and Automation; Intelligent Robotics; Sähkötekniikan korkeakoulu; School of Electrical Engineering; Kyrki, Ville, Prof., Aalto University, Department of Electrical Engineering and Automation, Finland
    Over the years, significant advancements have occurred in robotic grasping and manipulation techniques, transitioning from early analytical methods reliant on explicit mathematical model of grasps to modern learning-based approaches capable of generating high-quality grasps across a broad spectrum of objects from a single image. However, many of these methods achieve such remarkable performance by making assumptions pertaining to the object's physical properties, including uniform rigidity and friction across the surface. These assumptions limit the effectiveness of such methods in handling more complex artefacts, such as multi-material or deformable objects, which are commonly encountered in domains such as healthcare and household tasks. This dissertation seeks to explore the potential of explicitly estimating and harnessing two crucial physical properties of the target objects -- surface friction and deformability -- to develop resilient grasp and manipulation planners beyond these assumptions. First, a probabilistic method is proposed to estimate the surface friction properties of a target object. This estimation method employs exploratory actions to obtain visuo-tactile feedback, which is then used to determine the friction coefficient values. The resulting comprehensive object representation, incorporating both shape and surface friction information, is then integrated into the grasp planning process to notably enhance the grasp success rate. Subsequently, the dissertation investigates how to harness object deformability in grasp planning, developing a generative, deformation-aware deep grasp synthesis approach that enables planning high-quality grasps while considering object stiffness. Simultaneously, the aim is to overcome the existing limitations of obstructive and time-consuming grasp evaluation techniques for deformable objects. To achieve this goal, a computationally inexpensive analytical approach and a novel grasp quality metric are proposed to facilitate the evaluation of grasps on deformable objects in a matter of seconds, significantly accelerating the data generation process. In addition to grasping, the dissertation also explores how to harness object deformability in deformable object manipulation task planning by first introducing a learning-based model to predict the interactions between a volumetric deformable tool and rigid objects, and then using the learned model in task planning. Finally, instead of object deformability, the focus shifts to soft robotic hands, where deformability is built into robotic grippers. Specifically, the dissertation investigates means of integrating position and contact force sensing capabilities into a soft robotic hand to grasp deformable objects safely without causing damage. Together, the results indicate that acquiring and harnessing knowledge of an object's physical properties beyond its shape increases the robustness and performance of grasp planning and manipulation planning methods. Therefore, the hope is that this dissertation will motivate roboticists to move beyond current assumptions and consider deeper object understanding when developing new grasping and manipulation approaches.
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    Photonic and Electronic Characterization of Two-dimensional Transition Metal Dichalcogenides
    (Aalto University, 2023) Shafi, Abde Mayeen; Mackenzie, David, Dr., Kyocera Tikitin Oy, Finland; Elektroniikan ja nanotekniikan laitos; Department of Electronics and Nanoengineering; Nanoscience and Advanced Materials; Sähkötekniikan korkeakoulu; School of Electrical Engineering; Lipsanen, Harri, Prof., Aalto University, Department of Electronics and Nanoengineering, Finland
    Two-dimensional (2D) transition metal dichalcogenides (TMDCs) hold promise for numerous unprecedented applications in nanophotonics, optoelectronics, and nanoelectronics, owing to their extraordinary electrical and optical properties. However, these materials still face several challenges, including limited light-matter interactions, low luminescent yield, reduced carrier mobility, and susceptibility to environmental changes. This thesis aims to address the aforementioned limitations by employing various advanced techniques to enhance the optical and electronic properties of these materials. In this thesis, the light-matter interaction in TMDCs is enhanced by realizing mixed-dimensional heterostructures. High-performance photonic and optoelectronic devices are constructed by investigating two distinct types of these heterostructures. Firstly, monolayer MoS2 is transferred onto AlGaAs nanowires to create a mixed-dimensional heterostructure. A significant enhancement in Raman and photoluminescence responses is achieved from the heterostructure attributed to the electromagnetic field confinement within the high refractive index nanowire. The heterostructure also exhibits optical anisotropy due to the 3-fold rotational symmetry breaking of MoS2 caused by the nanowire. Additionally, the fabricated phototransistor using this heterostructure demonstrates improved responsivity and detectivity. Secondly, another mixed-dimensional heterostructure is formed by epitaxially growing InP nanowires directly on MoS2. High-density nanowire growth is achieved while ensuring the stability of MoS2. This heterostructure generates strong second- and third-harmonic signals and, notably, 5th and 7th-order high-harmonic signals, opening up potential applications such as lasers and electro-optic modulators. In the subsequent part of the thesis, the electronic properties of TMDCs are investigated and tuned to fabricate high-performance electronic and optoelectronic devices. At first, the impact of high temperatures on multilayer MoTe2 field-effect transistors is systematically explored to determine the optimal annealing temperature for the devices and acquire a deeper understanding of the surface oxidation-mediated defect formation and hopping transport mechanism in MoTe2 devices. Furthermore, a straightforward technique is proposed that involves substrate engineering and Al2O3 passivation to enhance the performance of few-layer MoTe2 devices by introducing local tensile strain and reducing electron-phonon scattering in the channel. This results in significant improvements in carrier mobility and device quality. Lastly, a simple optical writing technique is employed to transform the semiconducting 2H phase of MoTe2 into the metallic 1T´ phase, resulting in improved third harmonic generation signals and the performance of optoelectronic devices. These findings show great promise for advancing integrated photonic and optoelectronic circuits based on 2D-TMDCs.
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    Neural Modelling of Audio Effects
    (Aalto University, 2023) Wright, Alec; Välimäki, Vesa, Prof., Aalto University, Department of Information and Communications Engineering, Finland; Informaatio- ja tietoliikennetekniikan laitos; Department of Information and Communications Engineering; Audio Signal Processing; Sähkötekniikan korkeakoulu; School of Electrical Engineering; Välimäki, Vesa, Prof., Aalto University, Department of Information and Communications Engineering, Finland
    Neural networks and other machine learning based approaches to audio effects processing have become increasingly popular in recent years. This thesis focuses on the design and training of neural network architectures for the emulation of specific analog audio devices from data. The digital emulation of analog audio devices is commonly known as virtual analog, and popular effects processing devices for virtual analog modelling include guitar amplifiers, distortion pedals, time-varying effects, and compressors. Whilst analytical methods based on circuit analysis are capable of producing realistic, efficient and accurate models of devices, these approaches are limited by the fact that creating a model of a specific device is time-consuming and requires expert knowledge. In contrast, neural network based methods allow for greater automation in the modelling process, and can be applied relatively easily to a range of devices as long as sufficient data is available. This thesis proposes a number of neural network based methods for audio effects modelling, and shows that they achieve excellent perceptual emulation quality. The proposed models include convolutional, recurrent and differentiable digital signal processing based architectures. There is a focus on models with low computational cost and low latency, such that they are suitable for real-time processing as part of a music production workflow. Methods for modelling Low-Frequency Oscillator (LFO) modulated time-varying effects, compressors, guitar amplifiers and distortions pedals are proposed. In addition to the neural network architectures themselves, this thesis also provides practical details and methods for training the models. This includes the proposal and validation of a novel perceptually motivated pre-emphasis filter, used to model non-linear audio effects processing. Additionally a pruning method is applied and shown to achieve significant reduction in model size and inference cost for guitar amplifier and distortion effects modelling. Finally, this thesis presents a novel method for the task of modelling non-linear audio effects processing when paired training data is unavailable. This allows for complex non-linear effects processing to be emulated from recordings, whilst requiring no knowledge of the specific devices used to create the recording.
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    Secret Key Generation for Secure Wireless Internet of Things
    (Aalto University, 2023) Hentilä, Henri; Informaatio- ja tietoliikennetekniikan laitos; Department of Information and Communications Engineering; Sähkötekniikan korkeakoulu; School of Electrical Engineering; Koivunen, Visa, Prof., Aalto University, Department of Information and Communications Engineering, Finland
    In the Internet of Things (IoT), hundreds or even thousands of devices with wireless connectivity and typically equipped with sensors are communicating over shared radio spectrum. Applications of IoT include smart homes and cities, monitoring environment and radio spectrum, machine-type communications, and well-being. Ensuring the security of data in IoT is a serious challenge. Existing secrecy technologies, such as traditional encryption based on computational secrecy, are seen as too computationally demanding. In particular, IoT devices are often battery-powered and must be energy efficient, imposing constraints on computation, communication and price. As a potential alternative to traditional encryption, the concept of physical-layer security has been proposed. Since it is implemented on the physical layer of a wireless system, rather than the application layer, physical-layer security is in principle no more demanding than non-secret communication. Instead of computational secrecy, physical-layer security is based on informationtheoretic secrecy, which has provable secrecy guarantees regardless of an adversary's computational power. Thus, information-theoretic secrecy cannot be broken by e.g. quantum computers. On the other hand, it also has a number of drawbacks that may make its implementation challenging in practice, such as relying on knowledge of the adversary's channel. In this thesis, theory and methods for hybrid secrecy systems are developed by combining both information-theoretic secrecy and computational secrecy. Hence, many of the drawbacks of using either system in isolation may be avoided. In such a hybrid system, a secret key (SK) is first generated based on information-theoretic secrecy, with the SK subsequently used in a lightweight symmetric-key encryption algorithm to achieve secure communication. The thesis focuses on the secret key generation (SKG) problem, particularly when it is subject to constraints on computational resources and communication. Short blocklength processing used in low-latency and high reliability communications is of particular interest. The contributions of the thesis are two-fold. First, theoretical bounds for the SKG problem in the finite-blocklength regime are established. Specifically, upper and lower bounds on the rate at which SKs can be generated are derived, both with and without constraints on communication. These new bounds refine existing bounds to yield more accurate information at short blocklengths. Second, practical SKG protocols to be used for IoT are designed. These protocols exploit the random and reciprocal nature of wireless channels to derive the key from channel coefficient estimates. One protocol is based entirely on the quantization of the channel estimates, with no error correction. This allows for a very low computation and communication overhead, at the cost of a higher bit error rate (BER) in the generated keys. Another protocol uses error correction based on polar codes to achieve competitive key rates at short blocklengths for arbitrary BERs.
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    Integrated True-Time-Delay Beamforming Receivers
    (Aalto University, 2023) Spoof, Kalle; Kosunen, Marko, Dr., Aalto University, Department of Electronics and Nanoengineering, Finland; Unnikrishnan, Vishnu, Dr., Tampere University, Finland; Elektroniikan ja nanotekniikan laitos; Department of Electronics and Nanoengineering; Sähkötekniikan korkeakoulu; School of Electrical Engineering; Ryynänen, Jussi, Prof., Aalto University, Finland
    Advances in complementary metal-oxide-semiconductor (CMOS) integrated circuit (IC) technology have enabled the sophisticated wireless communication systems in use today. To respond to the demand for ever increasing data traffic volumes, the performance of these systems needs to improve to increase the capacity of data transfer. Beamforming is one of the technologies enabling improvements in the upcoming 5G communication systems. Beamforming with antenna arrays allows increased data throughput through spatial multiplexing, lower energy consumption through directed radio transmission and in-band spatial filtering for relaxed dynamic range and, therefore, power requirements. The often used implementation of beamforming with phased arrays limits the instantaneous bandwidth due to the use of the narrow-band approximation of propagation delay as phase shift. This bandwidth limitation can be overcome by replacing the beamforming phase shifts with true-time-delays (TTDs). Solutions for TTD beamforming are thus required to enable beamforming also for wideband radio systems. This thesis explores resampling true-time-delays as an integrated solution for beamforming receivers. The resampling TTDs are demonstrated with two prototype receiver ICs. The first prototype in 28-nm FD-SOI CMOS verified the resampling TTDs as a part of a radio frequency (RF) receiver front-end. The prototype achieved an 800 MHz instantaneous beamformed bandwidth across a 0.6--4 GHz frequency range with area and power consumption that is an order of magnitude lower compared to prior solutions. A second prototype in 22-nm FD-SOI CMOS demonstrated a beamforming receiver based on the resampling TTDs that can be reconfigured between analog and digital beamforming modes. This reconfigurability is achieved by integrating an ADC with the TTD. The second prototype achieved beamforming for a 2 GHz instantaneous bandwidth reaching 100 % fractional bandwidth at the low end of the 1--6 GHz frequency range. The second prototype was also used to demonstrate TTD beam-nulling which enables a frequency-independent notch direction for improved in-band spatial filtering. The implementations demonstrate the benefits of the resampling true-time-delays.