Characterization and Emulation of Low-Voltage Power Line Channels for Narrowband and Broadband Communication

The demand for smart grid and smart home applications has raised the recent interest in power line communication (PLC) technologies, and has driven a broad set of deep surveys in low-voltage (LV) power line channels. This book proposes a set of novel approaches, to characterize and to emulate LV power line channels in the frequency range from0.15to 10 MHz, which closes gaps between the traditional narrowband (up to 500 kHz) and broadband (above1.8 MHz) ranges

Characterization and Emulation of Low-Voltage Power Line Channels for Narrowband and Broadband Communication

The demand for smart grid and smart home applications has raised the recent interest in power line communication (PLC) technologies, and has driven a broad set of deep surveys in low-voltage (LV) power line channels. This book proposes a set of novel approaches, to characterize and to emulate LV power line channels in the frequency range from0.15to 10 MHz, which closes gaps between the traditional narrowband (up to 500 kHz) and broadband (above1.8 MHz) ranges

Emulation of Narrowband Powerline Data Transmission Channels and Evaluation of PLC Systems

This work proposes advanced emulation of the physical layer behavior of NB-PLC channels and the application of a channel emulator for the evaluation of NB-PLC systems. In addition, test procedures and reference channels are proposed to improve efficiency and accuracy in the system evaluation and classification. This work shows that the channel emulator-based solution opens new ways toward flexible, reliable and technology-independent performance assessment of PLC modems

Impulsive Noise Characterization in Narrowband Power Line Communication

Currently, narrowband Power line communication (PLC) is considered an attractive communication system in smart grid environments for applications such as advanced metering infrastructure (AMI). In this paper, we will present a comprehensive comparison and analysis in time and frequency domain of noise measured in China and Italy. In addition, impulsive noise in these two countries are mainly analyzed and modeled using two probability based models, Middleton Class A (MCA) model and α stable distribution model. The results prove that noise measured in China is rich in impulsive noise, and can be modeled well by α stable distribution model, while noise measured in Italy has less impulsive noise, and can be better modeled by the MCA model

Characterization and Emulation of Low-Voltage Power Line Channels for Narrowband and Broadband Communication

This thesis proposes a set of novel approaches to characterize and to emulate LV power line channels in the frequency range from 0.15 to 10MHz, which close gaps between the traditional narrowband (up to 500 kHz) and broadband (above 1.8MHz) ranges

Upgrading the Power Grid Functionalities with Broadband Power Line Communications: Basis, Applications, Current Trends and Challenges

This article reviews the basis and the main aspects of the recent evolution of Broadband Power Line Communications (BB-PLC or, more commonly, BPL) technologies. The article starts describing the organizations and alliances involved in the development and evolution of BPL systems, as well as the standardization institutions working on PLC technologies. Then, a short description of the technical foundation of the recent proposed technologies and a comparison of the main specifications are presented; the regulatory activities related to the limits of emissions and immunity are also addressed. Finally, some representative applications of BPL and some selected use cases enabled by these technologies are summarized, together with the main challenges to be faced.This work was financially supported in part by the Basque Government under the grants IT1426-22, PRE_2021_1_0006, and PRE_2021_1_0051, and by the Spanish Government under the grants PID2021-124706OB-I00 and RTI2018-099162-B-I00 (MCIU/AEI/FEDER, UE, funded by MCIN/AEI/10.13039/501100011033 and by “ERDF A way of making Europe”)

A Fast Blind Impulse Detector for Bernoulli-Gaussian Noise in Underspread Channel

The Bernoulli-Gaussian (BG) model is practical to characterize impulsive noises that widely exist in various communication systems. To estimate the BG model parameters from noise measurements, a precise impulse detection is essential. In this paper, we propose a novel blind impulse detector, which is proven to be fast and accurate for BG noise in underspread communication channels.Comment: v2 to appear in IEEE ICC 2018, Kansas City, MO, USA, May 2018 Minor erratums added in v

Multichannel power line communication

Power line communication (PLC) is the technology in which the data signals of a communication system are transmitted through the conductors of a power delivery infrastructure. The unique environment of the PLC channels create specific challenges and requirements, which need to be modeled and analyzed properly in order to obtain a clear understanding of the communication system as well as attaining the ability to further improve the performance and reliability of the transmission. Moreover, the demand for increased data throughput as well as increased reliability and robustness of the transmission is of fundamental importance in any communication system as it is in PLC systems. In order to address these challenges and demands, the concept of multichannel PLC is studied and developed in this thesis. Multichannel PLC in this context is referred to the transmission of multiple information-carrying signals though the power line channel from one source to one destination. We study multiple scenarios of multichannel data transmission in order to cover the diverse situations and requirements of a PLC transmission. One of the multichannel scenarios discussed in this thesis is the multiple-input multiple-output (MIMO) transmission, in which multiple data signals are transmitted via spatially separated PLC channels. Another scenario discussed in this thesis is the cooperative transmission between the source and destination of a PLC system by means of intermediate relay nodes in the network. Finally, the multiband transmission by utilizing different parts of the available PLC spectrum is studied. The core objective of this thesis is to develop and study novel algorithms and models to address the challenges and problems introduced in different scenarios of the multichannel PLC. These problems can be categorized as the channel selection problem for MIMO transmission, the relay selection problem for the cooperative communication, and the spectrum assignment problem for the multiband transmission. The basis of all these problems is a decision making problem, which can greatly influence the performance of the system. To address these decision making problems, a powerful mathematical tool, namely the multi-armed bandit model, is used to model the different problems emerging in different scenarios of the multichannel PLC. This modeling approach is then used as a building block for developing machine learning algorithms in order to solve the aforementioned selection problems. Finally, novel machine learning algorithms are developed and their performances are analyzed and assessed. It is shown that the machine learning approach can considerably improve the performance of the multichannel PLC systems compared to the existing state of the art approaches, by enabling the selecting agent, i.e. the PLC transmitter, to perform intelligent decisions which improves the overall performance.Die Power-Line-Communication (PLC) ist die Technologie, bei der die Datensignale eines Kommunikationssystems über die Leiter einer Energieversorgungsinfrastruktur übertragen werden. Die einzigartige Umgebung der PLC-Kanäle stellt konkrete Herausforderungen und Anforderungen dar, die modelliert und analysiert werden müssen, um ein klares Verständnis des Kommunikationssystems zu erhalten und die Fähigkeit zur Verbesserung der Leistung und Zuverlässigkeit der Übertragung zu erreichen. Darüber hinaus ist in Kommunikationssystem die Nachfrage nach erhöhtem Datendurchsatz, sowie erhöhter Zuverlässigkeit und Robustheit der Übertragung von grundlegender Bedeutung. Um diesen Herausforderungen und Anforderungen gerecht zu werden, wird in dieser Arbeit das Konzept der Mehrkanal-PLC untersucht und weiterentwickelt. Die Mehrkanal-PLC wird in diesem Zusammenhang auf die Übertragung mehrerer informationstragenden Signale über den PLC-Kanal von einer Quelle zu einem Ziel bezogen. Wir untersuchen mehrere Szenarien der Mehrkanal-Datenübertragung, um die vielfältigen Anforderungen einer PLC-Übertragung zu behandeln. Eines der in dieser Arbeit besprochenen Mehrkanal-Szenarien ist die Multiple-Input-Multiple-Output-Übertragung (MIMO), bei der mehrere Datensignale über räumlich getrennte PLC-Kanäle übertragen werden. Ein weiteres Szenario, das in dieser Arbeit diskutiert wird, ist die kooperative Übertragung zwischen der Quelle und dem Ziel eines PLC-Systems mittels Zwischenrelais als Knoten im Netzwerk. Schließlich wird die Multiband-Übertragung unter Verwendung unterschiedlicher Teile des verfügbaren PLC-Spektrums untersucht. Das Kernziel dieser Arbeit ist es, neuartige Algorithmen und Modelle zu entwickeln und zu untersuchen, um die Herausforderungen und Probleme zu lösen, die in verschiedenen Szenarien der Mehrkanal-PLC existieren. Diese Probleme sind als das Kanalauswahlproblem für die MIMO-Übertragung, das Relaiauswahlproblem für die kooperative Kommunikation und das Spektrum-Zuweisungsproblem für die Multibandübertragung kategorisiert werden. Die Basis all dieser Probleme ist ein Entscheidungsproblem, das die Leistungsfähigkeit des Systems stark beeinflussen kann. Um diese Probleme lösen zu können, wird ein mathematisches Werkzeug, nämlich das mehrarmige Bandit-Modell, verwendet, um die verschiedenen Probleme zu modellieren, die sich in verschiedenen Szenarien der Mehrkanal-PLC ergeben. Dieser Modellierungsansatz wird als Baustein für die Entwicklung von maschinellen Lernalgorithmen verwendet, um die zuvor beschriebenen Auswahlprobleme zu lösen. Schließlich werden neuartige maschinelle Lernalgorithmen entwickelt und ihre Leistungen analysiert sowie bewertet. Es zeigt sich, dass der maschinelle Lernansatz die Leistungsfähigkeit der Mehrkanal-PLC-Systeme im Vergleich zu den bestehenden Ans\"atzen des Standes der Technik erheblich verbessern kann, indem es dem Auswahlagenten, d.h. dem PLC-Sender, ermöglicht, intelligente Entscheidungen durchzuführen, die die Gesamtleistung verbessern

Machine Learning Tips and Tricks for Power Line Communications

4openopenTonello A.M.; Letizia N.A.; Righini D.; Marcuzzi F.Tonello, A. M.; Letizia, N. A.; Righini, D.; Marcuzzi, F