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Waveforms for sub-THz 6G: Design Guidelines
No full textThe projected sub-THz (100 - 300 GHz) part of the upcoming 6G standard will require a careful design of the waveform and choice of slot structure. Not only that the design of the physical layer for 6G will be driven by ambitious system performance requirements, but also hardware limitations, specific to sub-THz frequencies, pose a fundamental design constraint for the waveform. In this contribution, general guidelines for the waveform design are given, together with a non-exhaustive list of exemplary waveforms that can be used to meet the design requirements
Distributed MIMO Systems for 6G
No full textThis study focuses on Distributed MIMO (D-MIMO) systems and provides a discussion about their role in next generation networks. The paradigm shift to distributed networks offers great potential to address the 6G requirements, through macro diversity. As 6G scenarios and use cases continue to emerge, new challenges are likely to arise that may affect the widespread imp-lementation of D-MIMO. To address those, different deployment options have been proposed for roll-out considerations. They are composed of several sub-components that can be categorized as (i) wireless or wired fronthaul/backhaul, (ii) analog or digital signals, (iii) distributed or centralized processing, and (iv) coherent or non-coherent transmission. To facilitate standardization efforts, we provide 3GPP-aligned terminology for network nodes, multi-point transmission and reception schemes. In order to enable large-scale implementation of D-MIMO systems, it is important to determine the needed amount of distribution, develop practical solutions for high-frequency bands, and ways to convey data that meet the transport requirements. On this regard, we discuss key enablers and present simulation results for D-MIMO systems towards 6G. In particular, we present solutions for D-MIMO networks in dynamic scenarios related to channel estimation and layer-l mobility considering coherent and non-coherent joint transmission, and analog fronthaul implementation using analog-radio-over-fiber that are promising for high (upper mm-Wave and (sub-)THz) carrier frequencies, as well as integrated access and backhaul, network-controlled repeaters, and reconfigurable intelligent surfaces that are possible enablers for cost-efficient network densification at both low (cm-Wave, lower mm-Wave) and high carrier frequencies
Retrieving cloud ice masses from geostationary images with neural networks
Get PDFClouds are essential to the Earth\u27s energy budget and atmospheric circulation. Despite this, many cloud parameters are poorly known, including the mass of frozen hydrometeors. On the one hand, there will be specialized satellite missions targeting such hydrometeors. On the other hand, existing satellite data can be leveraged. There should be a particular interest in using geostationary satellite observations since they provide continuous coverage. Traditionally, retrievals of cloud ice masses from geostationary measurements require solar reflectances, ignore any spatial correlations, and solely retrieve the vertically-integrated ice mass density, known as the ice water path.This thesis challenges the traditional approach by applying supervised learning against CloudSat collocations, the only existing satellite mission targeting ice clouds. A set of neural networks is assembled to compare the performance of using different visible or infrared channels as retrieval input as well as the added value of using spatial context. The retrievals are probabilistic, in the sense that all neural networks predict quantiles to estimate the retrieval irreducible uncertainty, and thus represent the state of the art for atmospheric retrievals.With several spectral channels, infrared retrievals are found to have a similar performance compared to the peak accuracy offered by the combination of visible and infrared channels. However, the infrared-only retrievals enable a consistent diurnal performance. The use of spatial information reinforces the retrievals, which is demonstrated by the ability to provide skilful three-dimensional estimates of ice masses, known as ice water content, from only one infrared channel. The latter retrieval scheme is supported by an extensive validation with independent measurements.These neural network-based retrievals offer the possibility to derive new insights into cloud physics, reduce present ice cloud uncertainties, and validate climate models. Ideally, such retrieval schemes will complement the sparse measurements from specialized instruments. Finally, this thesis contains the groundwork for executing retrievals on multidecadal geostationary observations, offering unprecedented spatially and temporally continuous three-dimensional data for the tropics and mid-latitudes. The implementation of these ongoing retrievals is publicly released as part of the Chalmers Cloud Ice Climatology
RIS-Enabled and Access-Point-Free Simultaneous Radio Localization and Mapping
No full textIn the upcoming sixth generation (6G) of wireless communication systems, reconfigurable intelligent surfaces (RISs) are regarded as one of the promising technological enablers, which can provide programmable signal propagation. Therefore, simultaneous radio localization and mapping (SLAM) with RISs appears as an emerging research direction within the 6G ecosystem. In this paper, we propose a novel framework of RIS-enabled radio SLAM for wireless operation without the intervention of access points (APs). We first design the RIS phase profiles leveraging prior information for the user equipment (UE), such that they uniformly illuminate the angular sector where the UE is probabilistically located. Second, we modify the marginal Poisson multi-Bernoulli SLAM filter and estimate the UE state and landmarks, which enables efficient mapping of the radio propagation environment. Third, we derive the theoretical Cram\ue9r-Rao lower bounds on the estimators for the channel parameters and the UE state. We finally evaluate the performance of the proposed method under scenarios with a limited number of transmissions, taking into account the channel coherence time. Our results demonstrate that the RIS enables solving the radio SLAM problem with zero APs, and that the consideration of the Doppler shift contributes to improving the UE speed estimates
Low-Density Parity-Check Codes and Spatial Coupling for Quantitative Group Testing
No full textA non-adaptive quantitative group testing (GT) scheme based on sparse codes-on-graphs in combination with low-complexity peeling decoding was introduced and analyzed by Karimi et al.. In this work, we propose a variant of this scheme based on low-density parity-check codes where the BCH codes at the constraint nodes are replaced by simple single parity-check codes. Furthermore, we apply spatial coupling to both GT schemes, perform a density evolution analysis, and compare their performance with and without coupling. Our analysis shows that both schemes improve with increasing coupling memory, and for all considered cases, it is observed that the LDPC code-based scheme substantially outperforms the original scheme. Simulation results for finite block length confirm the asymptotic density evolution thresholds
Human-Data Interaction (HDI) and blockchain: an exploration of the open research challenges for the construction community
No full textChallenges for human-data interaction (HDI) have not yet been contextualized within blockchain implementation in construction. In this positional paper, a focus group accepts the EC3 HDI Committee’s working definition of construction specific HDI, and identifies technical (immutability, data storage, transparency, system design, integrating technologies), non-technical (ethics, economic models, environmental, political, social), and overlapping (governance, data usage, data analysis, and data control) factors to be considered in the intersection of HDI and blockchain. Those considerations led to open questions for future research efforts – e.g., regarding what data types (and the associated HDI) are suitable when implementing blockchain in the built environment
An enhanced semi-analytical estimation of tool-chip interface temperature in metal cutting
Get PDFAn accurate estimation of the temperature distribution on tool surfaces is of great industrial importance; without it, a reliable prediction of tool wear in machining, especially thermally-induced wear mechanisms such as dissolution-diffusion and oxidation, is deemed impossible. This has promoted the development of semi-analytical models for simulation of the tool-chip interface temperature, which are less time-intensive and reasonably accurate. This study aims to present an enhanced prediction of the tool-chip interface temperature within the context of the available semi-analytical solutions of the heat conduction-advection problem with a moving heat source. A novel approach is presented to obtain the variable heat flux along the tool-chip interface based on a non-uniform contribution of generated heat in the sticking and sliding zones during chip flow. The capability of the enhanced model to simulate the temperature distribution is demonstrated for machining C45 and C50 plain carbon steels using uncoated carbide tools. The predictions are validated against the results of experimental orthogonal cutting tests for the same cutting conditions. A comparative analysis is then performed to underline the importance of incorporating the variable heat flux for reliable predictions of the maximum interface temperature and its location on the rake face. The outlook for future developments is also highlighted
Plasmonic polymer nanoantenna arrays for electrically tunable and electrode-free metasurfaces
No full textElectrically tunable metasurfaces and interrelated nanofabrication techniques are essential for metasurface-based optoelectronic applications. We present a nanofabrication method suitable for various types of plasmonic polymer metasurfaces including inverted arrays of nanoantennas. Inverted metasurfaces are of particular interest since the metasurface itself can work as an electrode due to its interconnected nature, which enables electrical control without adopting an additional electrode. In comparison with inverted nanodisk arrays that support relatively weak resonance features, we show that inverted nanorod arrays can possess stronger resonances, even comparable with those of nanorod arrays. The origin of plasmon resonances in inverted arrays is systematically investigated using finite-difference time-domain (FDTD) simulations. Further, we demonstrate electrically tunable electrode-free metasurface devices using polymer inverted nanorod arrays, which can operate in the full spectral range of the material including the mid-infrared region
Model Predictive Control for\ua0Safe Autonomous Driving Applications
No full textAlthough Model Predictive Control is widely used in motion planning and control for autonomous driving applications, accommodating closed-loop stability with respect to an arbitrary reference trajectory and avoidance of pop-up or moving obstacles is still an open problem. While it is well-known how to design a closed-loop stable MPC with respect to a reference trajectory that satisfies the system dynamics, this chapter discusses how to guarantee stability of a vehicle motion planner and controller when a user-provided arbitrary reference is used. Furthermore, the proposed MPC scheme enables recursive collision-avoidance constraint satisfaction in the presence of pop-up or moving obstacles (e.g., pedestrians, cyclists, human-driven vehicles), provided that their predicted future motion trajectory is available together with some uncertainty bound and satisfies some mild requirement. The proposed motion planner and controller is demonstrated through simulations
The Rise and Current Status of Polaritonic Photochemistry and Photophysics
Get PDFThe interaction between molecular electronic transitions and electromagnetic fields can be enlarged to the point where distinct hybrid light-matter states, polaritons, emerge. The photonic contribution to these states results in increased complexity as well as an opening to modify the photophysics and photochemistry beyond what normally can be seen in organic molecules. It is today evident that polaritons offer opportunities for molecular photochemistry and photophysics, which has caused an ever-rising interest in the field. Focusing on the experimental landmarks, this review takes its reader from the advent of the field of polaritonic chemistry, over the split into polariton chemistry and photochemistry, to present day status within polaritonic photochemistry and photophysics. To introduce the field, the review starts with a general description of light-matter interactions, how to enhance these, and what characterizes the coupling strength. Then the photochemistry and photophysics of strongly coupled systems using Fabry-Perot and plasmonic cavities are described. This is followed by a description of room-temperature Bose-Einstein condensation/polariton lasing in polaritonic systems. The review ends with a discussion on the benefits, limitations, and future developments of strong exciton-photon coupling using organic molecules