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Leveraging axis-aligned subspaces for high-dimensional Bayesian optimization with group testing

Bayesian optimization (BO ) is an effective method for optimizing expensive-to-evaluate black-box functions. While high-dimensional problems can be particularly challenging, due to the multitude of parameter choices and the potentially high number of data points required to fit the model, this limitation can be addressed if the problem satisfies simplifying assumptions. Axis-aligned subspace appro

Control of Capacity-Constrained Networks

This thesis concerns control of capacity-constrained networks. These systems involve many agents interconnected by a resource distribution network. The capacity to generate and distribute this resource is constrained. This applies, for instance, to power grids, communication networks, smart surveillance camera networks, and district heating networks. District heating networks in particular are the

Ray-tracing-assisted High-Resolution Parameter Estimation for Dynamic Millimeter-Wave Channels

An accurate description of the wireless channel is essential to the development of modern wireless systems. In order to mathematically model the propagation channel, one important prior step often done is high-resolution parameter estimation. The estimation accuracy of this step has a significant impact on how well the channel models can represent reality. In this paper, we address this by improvi

A Belief Propagation Algorithm for Multipath-Based SLAM with Multiple Map Features : A mmWave MIMO Application

In this paper, we present a multipath-based simultaneous localization and mapping (SLAM) algorithm that con-tinuously adapts mulitiple map feature (MF) models describing specularly reflected multi path components (MPCs) from flat surfaces and point-scattered MPCs, respectively. We develop a Bayesian model for sequential detection and estimation of interacting MF model parameters, MF states and mob

Circularly polarized sub-THz antenna design for distributed deployment

Sub-THz deployment is challenging due to high propagation losses, necessitating dense deployment. To reduce cost, RF signal can be distributed via plastic fiber to remote radio units to increase coverage area. In this paper, we propose an antenna-in-package concept for the single-layer substrate on low-cost embedded wafer level ball grid array (eWLB) packages. To suppress the distortion in the bro

Millimeter-wave Scattering from Building Facade : A Simulation and Verification Study

This paper presents millimeter-wave scattering from a building facade predominantly composed of windows. These windows are integrated into the walls, forming dihedral structures that reflect waves toward the incident angle. The scattered field resulting from the building facade is simulated using the two-bounce Geometrical-Physics (GO) method. We analyze the channel in power loss and arrival angle

Capacitive Cancellation in Compact Integrated Multi-GHz Differential Passive Baseband Filters

The anticipated introduction of multi-GHz channel bandwidths in 6G makes integrated passive baseband filters very attractive. This work presents techniques to obtain high stop-band attenuation in a compact 4.7-GHz 5th-order passive baseband filter. A lumped model of the filter inductors is derived, and a capacitive cancellation technique is proposed, along with techniques to reduce inductive coupl

Welcome to the Fifth International Workshop on Requirements Engineering for Well-Being, Aging, and Health

Welcome to the fifth edition of the REWBAH workshop, a satellite event of the IEEE International Requirements Engineering Conference (RE). The REWBAH workshop fosters discussion related to requirements engineering resulting from the need to build software systems that not only support healthcare, but also promote well-being, encourage patients and the population in general to live according to hea

Hybrid Precoder Design for Angle-of-Departure Estimation with Limited-Resolution Phase Shifters

Hybrid analog-digital beamforming stands out as a key enabler for future communication systems with a massive number of antennas. In this paper, we investigate the hybrid precoder design problem for angle-of-departure (AoD) estimation, where we take into account the practical constraint on the limited resolution of phase shifters. Our goal is to design a radio-frequency (RF) precoder and a base-ba

Vanilla Bayesian Optimization Performs Great in High Dimensions

High-dimensional problems have long been considered the Achilles' heel of Bayesian optimization. Spurred by the curse of dimensionality, a large collection of algorithms aim to make it more performant in this setting, commonly by imposing various simplifying assumptions on the objective. In this paper, we identify the degeneracies that make vanilla Bayesian optimization poorly suited to high-dimen

Radiation Efficiency and Gain Bounds for Microstrip Patch Antennas

This paper presents bounds on radiation efficiency and gain for microstrip patch antennas, demonstrating close alignment with the performance of classic antenna designs. These bounds serve as effective benchmarks for assessing antenna performance and evaluating trade-offs and design feasibility. The study particularly addresses the trade-off between miniaturization and performance by comparing bou

Power Allocation for Uplink Communications of Massive Cellular-Connected UAVs

Cellular-connected unmanned aerial vehicle (UAV) has attracted a surge of research interest in both academia and industry. To support aerial user equipment (UEs) in the existing cellular networks, one promising approach is to assign a portion of the system bandwidth exclusively to the UAV-UEs. This is especially favorable for use cases where a large number of UAV-UEs are exploited, e.g., for packa

Foraging on the wing for fish while migrating over changing landscapes : traveling behaviors vary with available aquatic habitat for Caspian terns

Background: Birds that forage while covering distance during migration should adjust traveling behaviors as the availability of foraging habitat changes. Particularly, the behavior of those species that depend on bodies of water to find food yet manage to migrate over changing landscapes may be limited by the substantial variation in feeding opportunities along the route. Methods: Using GPS tracki

Clustering and cross-linking of the wheat storage protein α-gliadin : A combined experimental and theoretical approach

Our aim was to understand mechanisms for clustering and cross-linking of gliadins, a wheat seed storage protein type, monomeric in native state, but incorporated in network while processed. The mechanisms were studied utilizing spectroscopy and high-performance liquid chromatography on a gliadin-rich fraction, in vitro produced α-gliadins, and synthetic gliadin peptides, and by coarse-grained mode

H-Infinity Control with Nearly Symmetric State Matrix

In this letter, we give an upper bound on the deviation from H-infinity optimality of a class of controllers as a function of the deviation from symmetry in the state matrix. We further suggest a scalar measure of symmetry which is shown to be directly relevant for estimating nearness to optimality. In connection to this, we give a simple analytical solution to a class of Lyapunov equations for tw

Mathematical Modeling of Brain Circuitry during Cerebellar Movement Control

Reconstruction of movement control properties of the brain could result in many potential advantages for application in robotics. However, a hampering factor so far has been the lack of knowledge of the structure and function of brain circuitry in vivo during movement control. Much more detailed information has recently become available for the area of the cerebellum that controls arm-hand movemen

Finite Element-Boundary Integral Simulation of Icing Effects on a Marine Radar Reflector

This paper presents simulations of the radar cross section for a marine corner reflector affected by icing as it is illuminated by 3 GHz marine radar. This is compared to the radar cross section for an unaffected reflector, and the consequences for radar range are investigated. To perform the simulations, a finite element-boundary integral hybrid method is used. The simulation code is based on sev

Dual Control by Reinforcement Learning Using Deep Hyperstate Transition Models

In dual control, the manipulated variables are used to both regulate the system and identify unknown parameters. The joint probability distribution of the system state and the parameters is known as the hyperstate. The paper proposes a method to perform dual control using a deep reinforcement learning algorithm in combination with a neural network model trained to represent hyperstate transitions.

Enhanced Effective Aperture Distribution Function for Characterizing Large-Scale Antenna Arrays

Accurate characterization of large-scale antenna arrays is growing in importance and complexity for the fifth-generation (5G) and beyond systems, as they feature more antenna elements and require increased overall performance. The full 3D patterns of all antenna elements in the array need to be characterized because they are in general different due to construction inaccuracy, coupling, antenna ar