[diss] Sähkötekniikan korkeakoulu / ELEC

Permanent URI for this collection

Browse

Recent Submissions

Now showing 1 - 20 of 1014
  • Item
    Median Plane Localization - Psychoaucustics and Spatial Audio Effects
    (Aalto University, 2024) Kim, Taeho; Informaatio- ja tietoliikennetekniikan laitos; Department of Information and Communications Engineering; Aalto Acoustics Lab; Sähkötekniikan korkeakoulu; School of Electrical Engineering; Pulkki, Ville, Prof., Aalto University, Department of Information and Communications Engineering, Finland
    This thesis investigates the perception of the elevation of sources in the median plane by monaural spectral cues and, correspondingly, the synthesis of virtual source elevation using audio signal processing techniques. The contribution of spectral cues to median plane localisation was examined by measuring directional band effects with a more comprehensive approach than in existing literature. Additionally, the ability to segregate two concurrent sound sources in the median plane by spectral cues was examined with subjective listening tests, resulting in a measure of angular differentiation using monaural spectral cues alone. The measure was found to be finer than in an earlier study. The study also investigated the impact of added broadband noise on short sounds on localization in the median plane. The research revealed that, under specific circumstances, introducing background noise before a short sound burst can significantly improve localisation accuracy and mitigate inaccurate front-biased elevation perception in the median plane. A novel method for creating the perception of sound elevation was developed by utilising relative HRTF envelope filters. These filters were produced to examine the effectiveness of macroscopic HRTF envelopes that omitted the fine spectral details of pinna cues. The studies found that robust elevation perception can be achieved through the spectral features found in macroscopic HRTF envelopes as well as directional bands. Moreover, these spectral features were then utilised as the elevation filters by applying them to the early reflection part of stereo room impulse responses, which was subjectively verified to create the vertically extended perception of the reverberant sound field with acceptable colouration. The present thesis thus demonstrates that the macroscopic HRTF envelopes and directional cues can be widely beneficial across individuals diversely; however, individual-specific pinna-related features introduced in HRTFs enable more precise median plane localisation via spectral detail.
  • Item
    Space-Saving Antenna Solutions for Mobile Devices
    (Aalto University, 2024) Varheenmaa, Harri; Lehtovuori, Anu, D.Sc. (Tech.), Aalto University, Department of Electronics and Nanoengineering, Finland; Ylä-Oijala, Pasi, Ph.D., 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
    Smartphones are an essential part of modern society and antennas have a vital role in the operation of the phone and mobile communications infrastructure. In recent years, smartphones with a full edge-to-edge screen and a metal rim have been the goal of the phone manufacturers but designing the antennas on such devices is demanding task. A full edge-to-edge screen significantly reduces the available room for antennas since antennas can then only be located on the rim. Compared to plastic rim, the metal rim increases the coupling, which decreases efficiency. Additionally, modern handhelds require multiple antennas to cover all of the required fifth-generation (5G) frequency bands, increase the data transfer rate, and reduce the hand effect. Implementing all necessary 5G antennas is challenging due to limited space, manufacturing cost constraints, and unavailability of decoupling structures. This thesis proposes non-conventional ways to implement antennas in limited space. First, still unused space for antenna is identified in back cover. The designed antenna achieves good performance despite the challenging position where there is only a 1-mm gap between the radiating element and the metallic battery. Noteworthily, as the back-cover antenna radiates toward the user the specific absorption rate (SAR) must be considered. This thesis proposes the following three different strategies for reducing the SAR by almost half without affecting the radiated power: specific geometry, a matching circuit, and an antenna cluster with properly calculated feeding weights. The second space-saving design is an eight-element sub-6 GHz multiple-input multiple-output antenna design that is suitable for a smartphone with a highly desirable full edge-to-edge screen and metal rim. Its compact size (17.9mm × 7mm) is achieved by bending the antenna slots. Due to three excited current modes, the frequency band is wide (3.4–6.1 GHz) and the total efficiency is high (58–95%). Additionally, manufacturing costs and even more space are saved with a simple structure that does not require any decoupling solutions. The third design proposed in this thesis saves space by integrating a sub-6 GHz antenna and a millimeter-wave (mmWave) antenna into the same volume. This shared-aperture antenna requires even less room since the sub-6 GHz and mmWave antennas have a wide frequency band (3.4–6 GHz and 26.5–29.5 GHz, respectively). Attributable to the high isolation (15.3 dB), these antennas do not interfere each other’s operation and the total efficiency is good (65–95%). Furthermore, the beam steering range of the mmWave antenna is ±}40◦. Additionally, the proposed shared-aperture antenna design is suitable for mobile devices with a full edge-to-edge screen and a metal rim. The antenna solutions developed in this thesis demonstrate how antennas can be integrated into crowded devices, where the usable space is minimal, by retaining the required technical performance while also considering the implementation aspects.
  • Item
    Audio Decomposition for Time Stretching
    (Aalto University, 2024) Fierro, Leonardo; Välimäki, Vesa, Prof., Aalto University, Department of Information and Communications Engineering, Finland; Informaatio- ja tietoliikennetekniikan laitos; Department of Information and Communications Engineering; Aalto Acoustics Lab, Audio Signal Processing group; Sähkötekniikan korkeakoulu; School of Electrical Engineering; Välimäki, Vesa, Prof., Aalto University, Department of Information and Communications Engineering, Finland
    Time-scale modification is a common audio signal processing task that involves changing the duration of a sound without altering its frequency content. This thesis explores transients and noise sounds in the context of audio processing and investigates the use of sound decomposition to improve the quality of time scaling for normal and extreme stretching factors. Traditionally, time-stretching methods often introduce artifacts, such as phasiness and transient smearing, especially when the stretching factor is large. To address the issue, this thesis introduced an improved method to decompose sounds into their constituent sine, transient, and noise components, and a different processing technique can be separately applied to each individual class. This allows for better preservation of transient features, even at extreme stretching factors, and improves the perceived quality of time-stretched audio signals compared to traditional methods. This thesis also presents an alternative audio-visual evaluation method for audio decomposition using an interactive audio player application, where access to the individual sinusoidal, transient, and noise classes is granted through a graphical user interface. This application aims at covering the shortcomings of misused objective metrics and promotes experimenting with the sound decomposition process by observing the effect of variations for each spectral component on the original sound and by comparing different methods against each other, evaluating the separation quality both audibly and visually. This thesis also discusses the motivation behind the use of the sines-transient-noise decomposition for time stretching by analyzing the performance drop in a well-known time-scale modification method due to incorrect transient and noise handling. This work shows that, by adopting the proposed three-way decomposition within its framework, the quality of the timestretching performance of such a method is increased. The noise component is typically overlooked by conventional time-scale modification methods. This thesis introduces a novel hybrid design using a deep learning model to generate the stretched noise component with high quality even for extreme stretching factors, when the sound is slowed down by more than four times as it happens for slow motion sport videos or synthesis of ambient music. Finally, a simple and effective solution named noise morphing is described, producing state-of-the-art results across a wide range of audio inputs and stretching factors.
  • Item
    Improving Live Video Streaming Performance for Smart City Services
    (Aalto University, 2024) El Marai, Oussama; Informaatio- ja tietoliikennetekniikan laitos; Department of Information and Communications Engineering; Sähkötekniikan korkeakoulu; School of Electrical Engineering; Manner, Jukka, Prof., Aalto University, Department of Information and Communications Engineering, Finland
    Our world is rapidly moving in all its aspects toward a more digitized and connected life, including transportation, education, farming, and healthcare. A major enabler for such transformation is ICT-related tremendous innovations in networking, computation, and storage, both in software and hardware at affordable prices. Owing to these phenomenal advances, many revolutionary paradigms, such as multi-access edge computing, self-driving vehicles, and Smart Cities, have emerged, promising rosy prospects and a flourishing future. An eminent feature of these futuristic technologies is automation, where objects can communicate (i.e., sending and receiving data), understand their environment, and adapt to changing conditions by taking the right decisions. Also, stringent requirements (e.g., low latency communication) might be needed by many services for their proper functioning. To successfully accomplish these tasks, many paradigms (e.g., software-defined networking and machine learning techniques) should be involved at different levels (e.g., network and decision-making levels). Most of today's applications and systems (e.g., over-the-top and surveillance platforms) require video streaming as a key technology. Video streaming applications rank as the most bandwidth-intensive services, especially when delivered at higher resolutions, such as FHD and 4K. Fortunately, 5G technology is already available and promises higher bandwidth that can reach up to 20GB. In addition, it requires huge data storage spaces when historical data is needed, which no longer becomes an issue with the dawn of edge and cloud computing. The target consumer (i.e., humans or machines) might demand heavy computation resources, often requiring GPU processing, which is also nowadays readily available and affordable. This dissertation is all about harnessing video streaming technology for enabling Smart City services and paradigms, such as self-driving vehicles. Towards this end, we start by addressing the problem of improving video streaming performance in terms of delivered video quality, stall-free sessions, and low latency streaming, for various services, including video streaming services and some use cases of self-driving vehicles. As data is the fuel that empowers most Smart City systems and services, we propose a cost-efficient and sustainable solution to create the digital twin of city roads, which mainly relies on video streaming data. The proposed solution represents an essential step towards realizing the Smart City paradigm and would create a valuable data asset that feeds and benefits various systems and domains such as intelligent transportation systems and tourism. Owing to the extreme importance of situational awareness in Smart Cities, notably in dense urban areas, we leverage the proposed digital twinning solution and machine learning techniques to raise the awareness of connected vehicles about their surroundings, as well as overall street awareness per defined regions while accounting for the amount of transmitted data over the network to avoid video streaming performance degradation.
  • Item
    Radio Wave Propagation Simulations Based On Point Clouds – Methods, Experimental Validations and Applications To Radio Link Design
    (Aalto University, 2024) Koivumäki, Pasi; Karttunen, Aki, Dr., Tampere University, Finland; Elektroniikan ja nanotekniikan laitos; Department of Electronics and Nanoengineering; Antennas and propagation; Sähkötekniikan korkeakoulu; School of Electrical Engineering; Haneda, Katsuyuki, Assoc. Prof. Aalto University, Department of Electronics and Nanoengineering, Finland
    The exponential increase in mobile data traffic has resulted in spectrum shortage at the sub-6 GHz frequencies. The fifth-generation (5G) of wireless technologies aims to solve this by utilizing the millimeter-wave (mm-wave) bands and denser base station deployment. Cellular coverage at mm-wave bands and the interference conditions of dense spatial re-use of frequency spectrum are not well known. To evaluate link performance and predict coverage, wave propagation at radio frequencies in various scenarios must be characterized. This thesis provides improved tools, methods, and insights for coverage simulations to plan future deployments of wireless networks. Radio channel measurements are essential to understanding propagation and coverage characteristics. This thesis presents insights obtained from radio channel measurements in emerging environments, the outdoor-to-indoor (O2I) case and an elevator shaft. In the former case, the role of scattering from outdoor and indoor features is evaluated at 4 GHz and 14 GHz. In the latter, an Universal Software Radio Peripheral-based channel sounder is developed for polarimetric wideband channel measurements in an elevator shaft at 2.45 GHz and 5.8 GHz. The results show that the elevator shaft is a polarization-selective environment, with attenuation differences of up to 20 dB between links polarized along different sides of the elevator shaft. In addition to measurements, site-specific propagation simulation is an important tool in understanding radio wave propagation and its effect on coverage. Simulation accuracy is affected by level of detail in model of the propagation environment. In this work, ray-tracing and ray-launching propagation simulation methods based on detailed laser-scanned point clouds are developed. A novel method for preparing raw point clouds for propagation simulations is presented and its positive effect on simulation accuracy demonstrated. Radio channel simulations utilizing point clouds are performed in outdoor, indoor and O2I scenarios and their accuracy validated against measurements for frequencies ranging from 4 GHz to 60 GHz. The last part of this thesis is dedicated to applications of point cloud-based radio channel simulations. Line-of-sight probability at mm-wave frequencies is evaluated for urban micro-cells in the presence of clutter typically unavailable in environment databases, e.g., pedestrians and vehicles, and a Poisson-process based model of LOS probability is verified with them. Additionally, simulated radio channel data is utilized to validate feasibility of employing coarse beam-searching performed at 4 GHz for more efficient mm-wave beam-steering at 86 GHz. Finally, site-specific simulations are utilized as a test environment for 28 GHz 5G mobile phone antenna evaluation.
  • Item
    Multi-Alternative Operation-Planning Study to Maximize the Profit of Wind Farm Business: Multi-Sector Market Assessment of a Nordic Case
    (Aalto University, 2024) Ahmadi Kordkheili, Ramin; Pourakbari-Kasmaei, Mahdi, Prof., Aalto University, Department of Electrical Engineering and Automation, Finland; Sähkötekniikan ja automaation laitos; Department of Electrical Engineering and Automation; Sähkötekniikan korkeakoulu; School of Electrical Engineering; Pouresmaeil, Edris, Prof., Aalto University, Department of Electrical Engineering and Automation, Finland
    The concerns over harmful impact of fossil fuels on the environment has led to increasing the share of renewable energies in the electricity generation. Wind farms as renewable sources of energy are replacing such fuels. These producers are considered more environmentally friendly; however, their generation levels are uncertain. This is because wind power production depends on the weather, particularly wind speed, which increases the challenges of integrating wind power into the electricity grid. In the past, wind farms were largely supported by subsidies, through which wind power production was purchased under fixed-price contracts. However, with the growth in wind farms' share of total electricity generation, these subsidies are decreasing. Therefore, wind farm operators must compete with other conventional producers in the market. Nonetheless, considering the stochastic nature of wind power production, such a situation represents a major challenge for wind farm operators. This is due to the dispatchable nature of conventional producers, which constitutes a considerable advantage. The day-ahead electricity market usually closes hours before the actual delivery of electricity. Consequently, wind farm producers participate in the electricity market with only predictions of their wind power production and thus are likely to face deviations between the amount they are required to deliver to the market and their actual wind power production at time of delivery. To help wind power operators manage the stochasticity in wind power production, this thesis pursues two main aims. The first is to study different markets—the day-ahead electricity market, balancing electricity market, gas market, heat market, and green hydrogen market—as possible platforms for wind farm operators to trade energy. The second aim is to investigate the potential of different facilities to increase the profit of wind farm owners. These facilities include electrical energy storage, gas storage, and different Power-to-X facilities. Such facilities provide wind farm operators with the flexibility to turn wind power into gas, heat, and green hydrogen.
  • Item
    Representation learning methods for robotic perception and learning — at the intersection of computational neuroscience and machine learning
    (Aalto University, 2024) Struckmeier, Oliver; 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
    Despite the progress made in artificial intelligence and robotics, researchers have yet to fully decode or replicate the mechanisms behind the remarkable ability of the human brain to extract effective and flexible representations from sensor stimuli. Although numerous established machine-learning methods claim inspiration from the brain, uncovering novel concepts from neuroscience can enable further progress in robotics and machine learning. Therefore, this thesis presents research at the intersection of machine learning, robotics, and neuroscience, with an emphasis on representation learning, and perception.  First, the thesis introduces work on learning linearly alignable representations using a coupled autoencoder setup. Learning such representations simplifies the computationally demanding task of comparing and aligning probability distributions, a core component of many machine learning methods. Empirical evaluation of the proposed approach demonstrates that it can significantly simplify the solution to the mathematical optimization problem underlying domain adaptation. The core of the thesis focuses on applying principles from neuroscience to improve state-of-the-art representation learning methods. Hand-crafted features and representations learned using multi-modal variational autoencoders and predictive coding are empirically compared in terms of their robustness and data efficiency in navigation and place-recognition tasks in various experiments. Following the superior performance of predictive coding in the performed experiments, this thesis presents a brain-inspired extension to the variational autoencoder framework. Enforcing a slowness prior on latent dynamics in the variational autoencoder facilitates data-efficiency in downstream tasks. Finally, we extend our findings from the domain of representation learning and perception to imitation learning. In the constraint setting of learning from observations only, existing methods are brittle and fail to recover the causal effects of expert actions when access to the target environment is limited. Applying the previously discussed brain-inspired principles to learn representations in state-action spaces solves this problem.  The results of the research presented in this thesis indicate that augmenting representation learning methods with principles from neuroscience can help build more data-efficient, robust, and flexible intelligent systems.
  • Item
    Spectrum-aware Human-Centric Sensing (HCS) using mmWave radars
    (Aalto University, 2024) Salami, Dariush; Informaatio- ja tietoliikennetekniikan laitos; Department of Information and Communications Engineering; Ambient Intelligence Group; Sähkötekniikan korkeakoulu; School of Electrical Engineering; Sigg, Stephan, Prof., Aalto University, Department of Information and Communications Engineering, Finland
    This thesis explores the field of Human-Centric Sensing (HCS) using Millimeter Wave (mmWave) Frequency-Modulated Continuous Wave (FMCW) radars, proposing methods based upon Artificial Intelligence (AI) and Machine Learning (ML) tailored for data acquired from the radars. The mmWave FMCW-based HCS applications are divided into three categories of coarse-grained (such as localization), medium-grained (such as gesturerecognition for Human-Computer Interaction (HCI)), and fine-grained (such as water quality estimation) based on their requirements which influence the approaches needed for them. A set of novel approaches are proposed for each, based on their requirements. The performance of these approaches is assessed through extensive experimental evaluations, providing valuable insights into the potential of mmWave radar technologies for real-world HCS applications. In the field of fine-grained sensing, a neural-network-based model is proposed for water quality estimation, which can identify the source of water with 100% accuracy and detect metallic contaminants even at low concentrations. In medium-grained sensing, the thesis presents extensive research on utilizing mmWave FMCW radars for gesture recognition. Three models are proposed for gesture recognition using constrained devices without the need for GPU. Among them, the proposed Tesla-Rapture system achieves an accuracy of 97% on a set of 21 classes of gestures, pushing the limits of medium-grained HCI systems in terms of both accuracy and computational complexity. The thesis further extends the work to multiple radars for recognizing gestures in occluded and cluttered environments, and shows that the system can still be used with reasonable accuracy for zero-shot gesture-recognition. Moreover, the thesis presents research on coarse-grained applications such as multi-people localization, where a clustering-based approach and a neural-network-based approach are proposed and compared to state-of-theart technologies in the field of localization. The radar-based approach can achieve an average error of 3 cm, outperforming the mechanism based on Large Intelligent Surface (LIS). Given the congestion in the Radio Frequency (RF) spectrum, the thesis proposes an RF sensing approach integrated into the 5G standard using the sidelink mechanism. Furthermore, an approach based on Reinforcement Learning (RL) is proposed to efficiently utilize the unused part of the spectrum for communication. In conclusion, this thesis provides a comprehensive investigation of the potential of mmWave radars for HCS proposing new approaches based on AI and ML for each category of applications. The proposed methods can serve as a valuable resource for researchers in these fields, and the study's findings can assist in the development of new and improved technologies for real-world applications.
  • Item
    Antenna mutual coupling and amplifier effects in transmission
    (Aalto University, 2024) Kutinlahti, Veli-Pekka; Lehtovuori, Anu, 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
    The oncoming fifth generation (5G) telecommunication standard utilizes multi-antenna systems to implement multiple-input multiple-output and beam-steering capabilities in most wireless devices, including mobile devices. This shift in transceiver architecture will introduce each antenna element with its own feed control, along with an amplifier and phase shifter chain. The high integration level of these components prohibits the use of traditional ferrite circulators as isolators between the components, introducing the non-ideality of active reflections in the antenna elements to the amplifier outputs. The change in amplifier load impedance causes variation in amplifier output power, linearity, efficiency and can possibly even cause breakage of components in extreme cases. This development is parallel to the fact that 5G will use higher frequencies and wider bandwidth signals, driving the development of innovative design methods to achieve wide-band high-gain antennas with beam-steering capability. The first part of the thesis describes optimizing different aspects of amplifier-antenna systems with mutual-coupling-induced mismatch. First, the equivalent isotropic radiated power (EIRP) of a 2x2 patch antenna array in an amplifier-antenna system is optimized through phase tuning. Phase tuning achieves a maximum 0.7-dB improvement in EIRP within the -3-dB beam steer range at 2.5 GHz, compared to progressive phase shift. Second, the 3rd order intermodulation is minimized with respect to the carrier by adjusting input feed power and phase in a two-tone excited 1x4 amplifier-antenna array, where the beam at each tone is independently steered. Optimization results in a 25-dB improvement in the signal-to-3rd-order-intermodulation ratio without decreasing far-field power density. However, this improvement comes at the cost of sacrificing beam integrity in terms of side-lobe level. Third, 3rd order intermodulation with respect to the carrier is minimized by antenna impedance matching using co-simulations of the amplifier and antenna. The second part considers the optimization of realized gain in antenna arrays. First, an antenna array driven with element-specific amplifiers with varying output impedance is examined. Changes in amplifier gain may lead to altered output impedance and increased mismatch in the antenna interface, a phenomenon often neglected. An iterative method that accounts for the change in impedance is introduced, resulting in increased realized gain. Second, a cluster array concept is proposed to achieve high coverage gain over a wider band compared to a simple patch antenna array with similar elements. The cluster array utilizes patch elements with different resonant frequencies and high inter-element coupling to achieve wide-band matching with feeding weight tuning.
  • Item
    Towards Efficient Robotic Manipulation of Deformable Objects by Learning Dynamics Models and Adaptive Policies
    (Aalto University, 2024) Blanco-Mulero, David; Alcan, Gokhan, Asst. Prof., Tampere University, Finland; 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
    Recent years have witnessed significant progress in developing intelligent robotic systems that are able to perform manipulation tasks. One reason for this success has been the advent of learning-based approaches, which driven by improvements in deep learning techniques, have endowed robots with greater generalisation capabilities to manipulate objects varying in shape, size, and texture. However, the majority of these accomplishments have been restricted to the domain of rigid objects, while our world is replete with diverse objects that deform when manipulated. This introduces a new set of challenges, such as the need for representing their deformation and adapting the robotic manipulation actions accordingly. Nevertheless, attempts have been made to improve the efficiency of current approaches by either reducing the number of interactions required to succeed in these tasks or reducing the amount of data collected in the real world using simulation engines. Although methods have been proposed for learning to manipulate deformable objects such as garments, their adaptation capabilities still remain limited. Therefore, this dissertation proposes methods to bridge the gap in the adaptive capabilities of robotic systems for manipulating a variety of materials and objects. More specifically, it investigates methods that can learn to efficiently manipulate deformable objects in simulation, transfer the learnt skills to the real world, and examine the challenges that arise when transferring these skills. To accomplish this, the thesis first investigates the representation and modelling of deformable object dynamics using data-driven approaches, resulting in two methods for modelling the dynamics using graph-based representations. Subsequently, the thesis continues by investigating methods for enabling the learning of policies that can adapt and generalise to different objects and material properties. Thus, the dissertation proposes two approaches: adapting manipulation primitives when performing high-level planning and implementing closed-loop feedback for adapting the actions according to the object's deformation. Finally, this thesis studies a major challenge limiting approaches that learn to manipulate deformable objects in simulation: the reality gap. Here, a benchmark data set is proposed to evaluate the gap when performing a dynamic manipulation task. The results of the work comprising this dissertation show that policies learnt in simulation can adapt to a wide variety of deformable objects and can efficiently manipulate them, where closed-loop feedback can mitigate the reality gap in these approaches. Consequently, approaches based on learning in simulation can enhance the adaptability of manipulation systems, where closed-loop feedback plays a vital role in successfully transferring the learnt skills to the real world.
  • Item
    Outlooks on Radio Transmitter Energy Efficiency and Ultra-Low Power Radio Transmitters
    (Aalto University, 2024) Pulkkinen, Mika; Halonen, Kari, Prof., Aalto University, Department of Electronics and Nanoengineering, Finland; Elektroniikan ja nanotekniikan laitos; Department of Electronics and Nanoengineering; Sähkötekniikan korkeakoulu; School of Electrical Engineering; Halonen, Kari, Prof., Aalto University, Department of Electronics and Nanoengineering, Finland
    The number of wireless electronic devices in the world continues to grow at a rapid pace. The wireless devices are powered by limited energy sources and require energy-efficient electronic circuitry to maximize the operating time. Radios can consume a significant share of the power budget of a wireless device. Researchers and designers have, therefore, innovated numerous ultralow power (ULP) radio transmitters and receivers. Such ULP transmitters have conventionally used mostly on-off keying (OOK), binary phase-shift keying (BPSK) or binary frequency-shift keying (BFSK). These modulation schemes enable low power consumption – even below 100 μW – as they only require low-complexity transmitter circuitry and a relatively low signal-to-noise ratio (SNR) for a given error probability. This thesis investigates the option of using M-ary pulse-position modulation (PPM) and differential PPM (DPPM) in ULP narrowband transmitters in lieu of the conventionally used modulation schemes. The goal is to evaluate whether or not they could achieve better energy efficiency. The benefits and disadvantages of PPM and DPPM are reviewed and their energy efficiency is compared with OOK, BPSK and BFSK in a new way. In ULP transmitters, the power amplifier and carrier synthesizer generally consume the most power. The new comparison method considers how the choice of modulation impacts the combined energy consumed by these blocks per bit. The results suggest that use of OOK, BPSK and BFSK can consume tens to hundreds of percents more energy per bit compared to PPM and DPPM. The M-ary PPM schemes are predicted to be particularly energy-efficient in low-output-power transmitters. To evaluate the energy efficiencies of transmitter implementations, a new figure of merit (FOM) is derived. In prior ULP transmitter publications, the energy efficiency FOMs have neglected the effect of noise bandwidth and the choice of modulation. However, it is practically the output power and noise bandwidth that together determine the SNR of the generated signal. Moreover, this SNR and the SNR required by the modulation scheme significantly impact the achievable uplink range. By accounting for these metrics in addition to the energy consumption per bit (EPB), an FOM is obtained that provides a more comprehensive view of transmitter energy efficiency than the comparison metrics that have been used before. Two ULP DPPM radio transmitter implementations are presented with measured results. The first one achieves one of the lowest EPBs while still enabling an uplink range of 30 meters. The second one consumes more energy per bit but enables an uplink range of up to 1 km. An FOM comparison with prior transmitters, including recent sub-mW Bluetooth Low Energy transmitters, suggests that the latter transmitter is state of the art in terms of energy efficiency. In addition to the transmitters, an experimental ULP capacitive gesture sensor interface is presented with measured results. It enables hand-sweep and push-gesture detection over a short range.
  • Item
    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.
  • Item
    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.
  • Item
    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.
  • Item
    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.
  • Item
    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.
  • Item
    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.
  • Item
    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.
  • Item
    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.
  • Item
    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.