90 research outputs found

    PLC for the smart grid: state-of-the-art and challenges

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    This paper aims to review systems and applications for power line communications (PLC) in the context of the smart grid. We discuss the main applications and summarise state-of-the-art PLC systems and standards. We report efforts and challenges in channel and noise modelling, as well as in state-of-the-art transmission technology approaches

    State-of-the-art in Power Line Communications: from the Applications to the Medium

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    In recent decades, power line communication has attracted considerable attention from the research community and industry, as well as from regulatory and standardization bodies. In this article we provide an overview of both narrowband and broadband systems, covering potential applications, regulatory and standardization efforts and recent research advancements in channel characterization, physical layer performance, medium access and higher layer specifications and evaluations. We also identify areas of current and further study that will enable the continued success of power line communication technology.Comment: 19 pages, 12 figures. Accepted for publication, IEEE Journal on Selected Areas in Communications. Special Issue on Power Line Communications and its Integration with the Networking Ecosystem. 201

    Network Convergence in Multicarrier Hybrid Cellular Network

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    In a multicarrier communication system with known channel state information at transmitter (CSIT), it is well-known that the water-filling power allocation scheme is optimal in achieving the Shannon capacity. However, in a multicarrier broadcast network (e.g. over-the-air TV network) without CSIT, the optimal power allocation among subcarriers is still unknown, largely due to the heterogeneity of the channel conditions associated with different receivers. In the first part of the thesis, the performance of a generic multicarrier broadcast network is thoroughly studied by exploiting the frequency diversity over subcarriers. In particular, the performance metric is first defined based on the relationship among broadcast transmission rate, coverage area and outage probability. In order to maximize the network performance, closed form expressions of the instantaneous mutual information (IMI) and the optimal power allocation schemes are derived for both low SNR and high SNR cases; upper and lower bounds are also provided to estimate broadcast coverage area in general SNR regime. Also we extend our discussion to the broadcast network with multiple collaborative transmitters. Extensive simulation results are provided to validate our analysis. In the second part of the thesis, we discuss the optimal performance of a generic broadcast cellular hybrid network. It is well known that the Dirty Paper Coding (DPC) achieves the channel capacity for multiuser degraded channels. However, the optimality of DPC remains unknown for non-degraded channel. Specifically, we derive the optimal interference pre-cancellation order for a DPC based broadcast and unicast hybrid network. Different DPC cancellation schemes are studied to maximize the hybrid capacity region. The conditions for each scheme being optimal are analytically derived. Both ergodic and outage capacity are considered as our performance metric. Our results show that the optimal interference pre-cancellation order varies with SNR and broadcast and unicast channel conditions. Moreover, in low SNR condition, the optimal power allocation scheme is derived to reach the maximal sum rate

    Reliable indoor power line communication systems: via application of advanced relaying processing

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    In this thesis, we focus on improving the performance of indoor power line communication (PLC) systems using relaying schemes. A method of modelling relay-involved PLC channels has been proposed. We study the optimal joint transceiver and relay power allocation problem for relay-assisted multicarrier indoor PLC systems. We transform the nonconvex problem into a group of sub-problems which can be efficiently solved using standard convex optimization techniques. The proposed schemes outperform conventional direct PLC systems

    Machine Learning Tips and Tricks for Power Line Communications

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

    Multichannel power line communication

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    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

    Policies for Carbon Energy Footprint Reduction of Overhead Multiple-Input Multiple-Output High Voltage Broadband over Power Lines Networks

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    The impact of different environmental policies on the broadband performance of overhead multiple-input multiple-output high-voltage/broadband over power lines (MIMO/HV/BPL) networks is investigated in this paper. The examined environmental policies focus on the carbon energy footprint reduction of overhead MIMO/HV/BPL networks while respecting their broadband character.The contribution of this paper is three-fold. First, the spectral and environmental performance of various configurations and topologies of overhead MIMO/HV/BPL networks is assessed with regard to respective spectral efficient (SE) and newly presented environmental efficient (EE) metrics. Second, further insights regarding the performance of overhead MIMO/HV/BPL networks highlight the better spectral and environmental performance of these networks against other today’s overhead HV/BPL networks, such as single-input single-output (SISO), single-input multiple-output (SIMO), or multiple-input single-output (MISO) ones. Third, the definition of appropriate environmental policies that optimize the coexistence of the three main sectors of concern, which are the Quality of Service (QoS) requirements, protection of existing radioservices and promotion of environmentally aware limits, is promoted. Towards that direction, the proposed SE/EE trade-off relation of this paper is expected to prove an extremely helpful SE/EE optimization technique.Citation: Lazaropoulos, A. G. (2015). Policies for Carbon Energy Footprint Reduction of Overhead Multiple-Input Multiple-Output High Voltage Broadband over Power Lines Networks. Trends in Renewable Energy, 1(2), 87-118. DOI: 10.17737/tre.2015.1.2.001

    LPTV-Aware Bit Loading and Channel Estimation in Broadband PLC for Smart Grid

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    Power line communication (PLC) has received steady interest over recent decades because of its economic use of existing power lines, and is one of the communication technologies envisaged for Smart Grid (SG) infrastructure. However, power lines are not designed for data communication, and this brings unique challenges for data communication over power lines. In particular for broadband (BB) PLC, the channel exhibits linear periodically time varying (LPTV) behavior synchronous to the AC mains cycle. This is due to the time varying impedances of electrical devices that are connected to the power grid. Another challenge is the impulsive noise in addition to power line background noise, which is due to switching events in the power line network. In this work, we focus on two major aspects of an orthogonal frequency division multiplexing (OFDM) system for BB PLC LPTV channels; bit and power allocation, and channel estimation (CE). First, we investigate the problem of optimal bit and power allocation, in order to increase bit rates and improve energy efficiency. We present that the application of a power constraint that is averaged over many microslots can be exploited for further performance improvements through bit loading. Due to the matroid structure of the optimization problem, greedy-type algorithms are proven to be optimal for the new LPTV-aware bit and power loading. Significant gains are attained especially for poor (i.e. high attenuation) channel conditions, and at reduced transmit-power levels, where the energy per bit-transmission is also low. Next, two mechanisms are utilized to reduce the complexity of the optimal LPTV-aware bit loading and peak microslot power levels: (i) employing representative values from microslot transfer functions, and (ii) power clipping. The ideas of LPTV-aware bit loading, complexity reduction mechanism, and power clipping are also applicable to non-optimal bit loading schemes. We apply these ideas to two additional sub-optimal bit loading algorithms that are based on even-like power distribution for a portion of the available spectrum, and demonstrate that similar gains in bit rates are achieved. Second, we tackle the problem of CE for BB PLC LPTV channels. We first investigate pilot based CE with different pilot geometry in order to reduce interpolation error. Block-type, comb-type, and incline type pilot arrangements are considered and a performance comparison has been made. Next we develop a robust CE scheme with low overhead that addresses the drawbacks of block-type pilot arrangement and decision directed CE schemes such as large estimation overhead for block-type pilot geometry, and difficulty in channel tracking in the case of sudden changes in the channel for decision directed approaches. In order to overcome these drawbacks, we develop a transform domain (TD) analysis approach to determine the cause of changes in the channel estimates, which are due to changes in the channel response or the presence of impulsive noise. We then propose a robust CE scheme with low estimation overhead, which utilizes pilot symbols placed widely apart and exploits the information obtained from TD analysis as a basis for switching between various CE schemes. The overhead of the proposed scheme for CE is low, and sudden changes in the channel are tracked affectively. Therefore, the effects of the LPTV channel and the impulsive noise on CE are mitigated. Our results indicate that for bit and power allocation, the proposed reduced complexity LPTV-aware bit loading with power clipping algorithm performs very close to the optimal LPTV-aware bit loading, and is an attractive solution to bit loading in a practical setting. Finally, for the CE problem, the proposed CE scheme based on TD analysis has low estimation overhead, performs well compared to block-type pilot arrangement and decision directed CE schemes, and is robust to changes in the channel and the presence of impulsive noise. Therefore, it is a good alternative for CE in BB PLC

    Dynamic Topology Estimation and Resource Allocation for Power Line Communication

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    Power line communication (PLC), which uses existing infrastructure of power delivery for data transfer, is regarded as an economical, pervasive and extensive communication solution for smart grid and home broadband applications. One of the challenges of applying communication technologies to power line network lies in acquirement of channel state information (CSI), which is dependent on network topology. Moreover, the knowledge of topology provides a basis for the design of routing protocols and power flow optimization. Therefore, efficient approaches for dynamic topology estimation are highly demanded. While dynamic routing and resource allocation enable high-speed and multi-tasking communication services over power lines. In this thesis, a dynamic topology estimation scheme for PLC is investigated, and a cross-layer routing and resource allocation scheme assisted by dynamic topology estimation is developed to improve the system performance. In the first contribution, a high-resolution and low-complexity dynamic topology estimation scheme for time-varying indoor PLC networks is proposed. The scheme consists of three parts: a) a time-frequency domain reflectometry (TFDR) based path length estimation method, which requires measurement at a single PLC modem and achieves a much higher resolution than the frequency domain reflectometry (FDR) based method; b) a node-by-node greedy algorithm for topology reconstruction, which is much more computationally efficient than the existing peak-by-peak searching algorithm; c) an impulsive noise assisted dynamic topology re-estimation method, which results in a significant complexity reduction over fixed-frequency re-estimation. In the second contribution, a cross-layer routing and resource allocation (RA) scheme assisted by dynamic topology estimation is proposed to optimize the system throughput of indoor PLC network with heterogeneous delay requirements. The proposed scheme provides a multi-layer solution, which conducts the network layer routing based on the result of PHY layer resource allocation which is constrained by the MAC layer queuing delay. With the dynamic topology estimation proposed in the first contribution, the routing can be solved centrally at the source, which is more robust against topology changes compared to distributed solutions. The proposed cross-layer RA scheme consists of subcarrier allocation (SA) to multiple users and power allocation (PA) to subcarriers satisfying heterogeneous delay requirements. It is demonstrated that the proposed centralized routing strategy achieves a much lower packet loss rate (PLR) than a distributed routing scheme; while with optimal RA, the system throughput is significantly improved compared to the routing schemes without considering RA
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