
Andrea M. Tonello- PhD
- Professor at Alpen-Adria-Universität Klagenfurt
Andrea M. Tonello
- PhD
- Professor at Alpen-Adria-Universität Klagenfurt
About
310
Publications
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5,622
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Introduction
Current institution
Additional affiliations
October 2015 - present
February 1997 - December 2003
January 2003 - October 2015
Publications
Publications (310)
Designing objective functions robust to label noise is crucial for real-world classification algorithms. In this paper, we investigate the robustness to label noise of an $f$-divergence-based class of objective functions recently proposed for supervised classification, herein referred to as $f$-PML. We show that, in the presence of label noise, any...
Stabilizing a 6DOF underactuated mechanical system ( $\mathbb {R}^{3} \times SO(3)$ ) without a cascade structure while utilizing a full-state feedback controller presents a significant challenge. Furthermore, due to the complexities of its dynamics and the degree of underactuation, designing an energy-shaping controller for such a system has not b...
This paper focuses on the parameterization of the multipath propagation model (MPM) for indoor broadband power line communications (PLC), which up to now has been established in an heuristic way. The MPM model was initially proposed in the PLC context for outdoor channels in the band up to 20 MHz, but its number of parameters becomes extremely larg...
This paper highlights the critical need to address the access impedance in power supplies used in power line communication (PLC) modems. Low values of access impedance of power supplies can significantly attenuate PLC signals at both the transmitter and receiver nodes, leading to substantial degradation in performance. To mitigate this issue, we pr...
This paper focuses on the parameterization of the multipath propagation model (MPM) for indoor broadband power line communications (PLC), which up to now has been established in an heuristic way. The MPM model was originally proposed for outdoor channels in the band up to 20 MHz, but its number of parameters becomes extremely large when used to mod...
In this paper, we introduce the Global Multi-Phase Path Planning (GMP
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) algorithm in planner problems, which computes fast and feasible trajectories in environments with obstacles, considering physical and kinematic constraints. Our approach utili...
In-band full-duplex (IBFD) is an attractive technology in broadband power line communication (BB-PLC) because it helps to improve spectral efficiency. However, IBFD is challenging since it requires additional hardware and advanced signal processing to mitigate self-interference (SI) signals. SI cancellation architectures and channel estimation tech...
Smart agriculture is an enabling technology addressing the increasing challenges of efficiency, sustainability, and quality of food production. It requires rich data from the farming area at high spatial and temporal resolution. Although remote sensing systems have become readily available recently, in-situ sensing is still required to capture impo...
This article introduces an innovative data-driven integral reinforcement learning (IRL) algorithm for the control of a class of underactuated mechanical systems. We propose a novel value function that allows shaping and learning the potential energy of an underactuated system and to drive it to a desired closed-loop potential energy. Consequently,...
In this paper, we propose a procedure to solve the controlled design for a class of underactuated mechanical systems. Our proposed method can be viewed as a sub-method of the IDA-PBC or Controlled Lagrangian approaches, with a particular focus on shaping the potential energy. By emphasizing potential energy shaping, we can effectively tackle the bo...
In this paper, the problem of determining the capacity of a communication channel is formulated as a cooperative game, between a generator and a discriminator, that is solved via deep learning techniques. The task of the generator is to produce channel input samples for which the discriminator ideally distinguishes conditional from unconditional ch...
The accurate estimation of the mutual information is a crucial task in various applications, including machine learning, communications, and biology, since it enables the understanding of complex systems. High-dimensional data render the task extremely challenging due to the amount of data to be processed and the presence of convoluted patterns. Ne...
In this paper, the problem of determining the capacity of a communication channel is formulated as a cooperative game, between a generator and a discriminator, that is solved via deep learning techniques. The task of the generator is to produce channel input samples for which the discriminator ideally distinguishes conditional from unconditional ch...
In this article, we consider the problem of distributed detection of a localized radio source emitting a signal. We consider that geographically distributed sensor nodes obtain energy measurements and compute cooperatively a statistic to decide if the source is present or absent. We model the radio source as a stochastic signal and deal with spatia...
One of the challenging problems in sensor network systems is to estimate and track the state of a target point mass with unknown dynamics. Recent improvements in deep learning (DL) show a renewed interest in applying DL techniques to state estimation problems. However, the process noise is absent which seems to indicate that the point-mass target m...
In this article, we tackle the problem of fully-distributed detection of a radio source emitting a signal in a fast fading scenario. We consider that geographically distributed sensor nodes obtain energy measurements and compute cooperatively and in a distributed fashion a decision metric for detecting if the source is present or absent without the...
Smart Grids (SG) envision the exchange of both power and data, enabling system and customers to generate and transfer energy in a more efficient and balanced way. Among the relevant communication technologies, we find Power-Line Communications (PLC), which allow for data transmission on the electrical cables used for power delivery. Despite the hos...
We propose an optimal destination scheduling scheme to improve the physical layer security (PLS) of a power-line communication (PLC) based Internet-of-Things system in the presence of an eavesdropper. We consider a pinhole (PH) architecture for a multi-node PLC network to capture the keyhole effect in PLC. The transmitter-to-PH link is shared betwe...
In this article, we tackle the problem of distributed detection of a radio source emitting a signal. We consider that geographically distributed sensor nodes obtain energy measurements and compute cooperatively a statistic to decide if the source is present or absent. We model the radio source as a stochastic signal and work with spatially statisti...
We are assisting at a growing interest in the development of learning architectures with application to digital communication systems. Herein, we consider the detection/decoding problem. We aim at developing an optimal neural architecture for such a task. The definition of the optimal criterion is a fundamental step. We propose to use the mutual in...
Probability density estimation from observed data constitutes a central task in statistics. Recent advancements in machine learning offer new tools but also pose new challenges. The big data era demands analysis of long-range spatial and long-term temporal dependencies in large collections of raw data, rendering neural networks an attractive soluti...
We are assisting at a growing interest in the development of learning architectures with application to digital communication systems. Herein, we consider the detection/decoding problem. We aim at developing an optimal neural architecture for such a task. The definition of the optimal criterion is a fundamental step. We propose to use the mutual in...
The development of optimal and efficient machine learning-based communication systems is likely to be a key enabler of beyond 5G communication technologies. In this direction, physical layer design has been recently reformulated under a deep learning framework where the autoencoder paradigm foresees the full communication system as an end-to-end co...
This paper presents a control-based trajectory generation approach for unmanned aerial vehicles (UAVs) under dynamic constraints. It exploits the concept of optimal control to find closed-form differential equations that satisfy any arbitrary dynamic limitation mapped into kinematic constraints. Pontryagin’s Minimum Principle applies to derive a se...
Several experiments and field trials have shown that deterministic components characterize the Power Line Communication (PLC) noise across multiple-conductors. This article aims at understanding the main origins of these noise components and evaluate several methods to characterize them statistically. The correlation, distance-correlation, mutual i...
Channel capacity plays a crucial role in the development of modern communication systems as it represents the maximum rate at which information can be reliably transmitted over a communication channel. Nevertheless, for the majority of channels, finding a closed-form capacity expression remains an open challenge. This is because it requires to carr...
The autoencoder concept has fostered the reinterpretation and the design of modern communication systems. It consists of an encoder, a channel, and a decoder block which modify their internal neural structure in an end-to-end learning fashion. However, the current approach to train an autoencoder relies on the use of the cross-entropy loss function...
In-band full-duplex (IBFD) is an attractive solution for increasing the throughput of Power Line Communication (PLC) systems. In IBFD, each network node is allowed to transmit and receive simultaneously in the same frequency band. This paper discusses the importance of defining figures of merit to analyze IBFD performance, which is often forgotten...
This aticle presents a novel recursive smooth trajectory (RST) generation algorithm for application in robotics and in particular for unmanned aerial vehicles (UAVs). RST builds the trajectory recursively as a smooth polynomial path, thus a closed form trajectory satisfying any arbitrary dynamic limitation that translates into kinematic constraints...
Recent advancements in generative networks have shown that it is possible to produce real-world-like data using deep neural networks. Some implicit probabilistic models that follow a stochastic procedure to directly generate data have been introduced to overcome the intractability of the posterior distribution. However, the ability to model data re...
We propose a mechanical system named swash mass pendulum (SMP) with application in robotics, and we develop a passivity-based control approach. The SMP is a pendulum made of a rigid shaft connected to a pair of cross-shafts where four swash masses can move under the action of servo mechanisms. The control objective is to stabilize the pendulum at a...
In this letter, an investigation of the very high frequency - ultra high frequency (VHF)-(UHF) wireless broadband indoor channel is carried out. In particular, a wireless channel measurement campaign in an indoor environment has been made, in order to characterise the path loss in a broad set of frequencies. The wireless channel is sounded by using...
The autoencoder concept has fostered the reinterpretation and the design of modern communication systems. It consists of an encoder, a channel, and a decoder block which modify their internal neural structure in an end-to-end learning fashion. However, the current approach to train an autoencoder relies on the use of the cross-entropy loss function...
We consider a small helicopter structure that is maneuvered through the control of moving masses. It is referred to as a swash mass helicopter (SMH). This paper addresses the trajectory tracking control problem for the SMH, with a specific focus on the decoupling change of coordinates of both rotational and translational dynamics.We propose a contr...
A key challenge in narrowband power line communications (NB-PLC) is the mitigation of impairments introduced by the correlated cyclostationary noise. The frequency-shift (FRESH) filtering approach has been recently proposed to reproduce a cyclostationary NB-PLC noise with characteristics similar to those obtained from field measurements. In this pa...
Leakage of information in power line communication (PLC) networks is a threat to privacy and security. A way to enhance security is to encode the transmitted information with the use of a secret key. If the communication channel exhibits common characteristics at both ends and these are unknown to a potential eavesdropper, then it is possible to lo...
Power line communication (PLC) is a growing technology which utilizes the existing pre-installed power delivery infrastructure for data transmission. While it is true that the history of PLC technology goes back to the beginning of the last century, when the first data transmission over power lines took place for low data rate control and monitorin...
In this paper, a new unmanned aerial vehicle (UAV) structure, referred to as swash mass UAV, is presented. It consists of a double blade coaxial shaft rotor and four swash masses that allow changing the orientation and maneuvering the UAV. The dynamical system model is derived from the Newton\textquotesingle s law framework. The rotational behavior...
A great deal of attention has been recently given to Machine Learning (ML) techniques in many different application fields. This paper provides a vision of what ML can do in Power Line Communications (PLC). We first and briefly describe classical formulations of the ML, and distinguish deterministic from statistical learning models with relevance t...
An effective approach to enhance the data rate in narrowband power line communication (NBPLC) system is multi-carrier modulation based on orthogonal frequency-division mul-tiplexing (OFDM) and multiple-input multiple-output (MIMO) transmission over multiple power line phases. A key challenge for achieving reliable communication over MIMO-OFDM NBPLC...
A great deal of attention has been recently given to Machine Learning (ML) techniques in many different application fields. This paper provides a vision of what ML can do in Power Line Communications (PLC). We firstly and briefly describe classical formulations of ML, and distinguish deterministic problems from statistical problems with relevance t...
The aim of the present work is to provide the theoretical fundamentals needed to monitor power grids using high frequency sensors. In our context, network monitoring refers to the harvesting of different kinds of information: topology of the grid, load changes, presence of faults and cable degradation. We rely on transmission line theory to carry o...
Signal relays in power line communication networks are usually implemented using the decode-and-forward protocol, which requires complex relays. In this paper, we propose a real time amplify-and-forward relay that is mainly based on an analog full duplex architecture. The speed of analog circuits enables the amplification of the incoming signal wit...
The main subject of this paper is the sensing of network anomalies that span from harmless impedance changes at some network termination to more or less pronounced electrical faults, considering also cable degradation over time. In this paper, we present how to harvest information about such anomalies in distribution grids using high frequency sign...
The focusing ability of the lens antennas can significantly contribute to perform precise radio localization with low complexity in a massive antennas array (MAA) system. Thus, by combining lens antennas with a MAA, we propose an approach for radio source localization through angle of arrival (AoA) estimation in a multipath propagation scenario. We...
The market projection for Internet of Things (IoT) systems is appealing for the Power Line Communication (PLC) technology. A massive growth and a pervasive presence of these IoT objects is expected in our everyday life. About 20 billion of IoT devices are forecasted to be installed in the next two years. PLC is a compelling technology that could be...
Leakage of information in power line communication networks is a threat to privacy and security both in smart grids and in-home applications. A way to enhance security is to encode the transmitted information with a secret key. Relying on the channel properties, it is possible to generate a common key at the two communication ends without transmitt...
The main subject of this paper is the sensing of network anomalies that span from harmless impedance changes at some network termination to more or less pronounced electrical faults, considering also cable degradation over time. In this paper, we present how to harvest information about such anomalies in distribution grids using high frequency sign...
The aim of the present work is to provide the theoretical fundamentals needed to monitor power grids using high frequency sensors. In our context, network monitoring refers to the harvesting of different kinds of information: topology of the grid, load changes, presence of faults and cable degradation. We rely on transmission line theory to carry o...
In recent times, massive antenna array technology has captured significant attention among wireless communication researchers. This is a field with strong potential to increase rates of data transfer; mitigate interference and serve a large number of users simultaneously. To contribute further to this emerging technology, this paper presents an app...
Disruptive technologies proposed for 5G wireless systems and the IoT hold promise of providing unprecedented localization capabilities for a wide range of application scenarios and target environments. This whitepaper summarizes the expected features and resulting properties of upcoming localization systems exploiting 5G and IoT technologies. It al...
Non-orthogonal multiple access (NOMA) has recently been proposed for dual-hop cooperative relaying power line communication (PLC) systems. Unlike conventional NOMA-PLC schemes which deploy NOMA only at the relay, this paper proposes to enhance the performance of such systems by implementing the principle of NOMA at both the source and relaying mode...
This paper focuses on MIMO Power Line Communication (PLC) to provide increased performance. In MIMO PLC, appropriate coupling methods are necessary in order to enable the effective injection of the signal through the broad band PLC channel so that high data rates can be achieved. In this paper, we want to analytically characterize strengths and wea...
Transmission line theory enables the bottom up study of networks based on wireline infrastructures. This technique is here applied to a simulator that brings together powerline communication networks with small radio cells ones in a hybrid paradigm: this allows to implement a study of channel capacity and communication quality based on the geometri...
Nowadays, multi-sensor networks are evolving into large scale networks with limited bandwidth and energy reservoirs. Hence, reducing the number of information exchanges among the sensors is an efficient approach to meet the stringent requirements of bandwidth and energy in the context of multisensor state estimation. In this paper, a surprisal base...
p>This paper presents the performance analysis of hybrid rat race coupler, widely used in radio frequency (RF)/wireless communication systems to couple the power in the desired way. The hybrid ring coupler consists of 4 ports, two for the input signals and two for the output signals, where sum and difference patterns of the applied two signals can...