This chapter provides an overview of the state of the art in channel characterization for power line communication (PLC). It sets the stage with an overview of basic power line topologies and characteristics of power line channels. The chapter discusses the channel models that fall into three main categories, namely deterministic, empirical and hybrid models, and the advantages and disadvantages of these approaches. It focuses on the low voltage (LV) PLC channel in both outdoor power distribution grids and in-home networks and dedicates to channel characterization of the medium voltage (MV) and the high voltage (HV) scenarios. The chapter discusses the characterization and modeling of multiple-input multiple-output (MIMO) PLC channels and presents the measurements and mathematical models for the noise experienced in PLC systems. It provides the main PLC channel characteristics in other scenarios, namely, the low voltage DC distribution grid scenario, the in-car scenario and the in-ship scenario.

Channel Characterization

Tonello A. M.;
2016-01-01

Abstract

This chapter provides an overview of the state of the art in channel characterization for power line communication (PLC). It sets the stage with an overview of basic power line topologies and characteristics of power line channels. The chapter discusses the channel models that fall into three main categories, namely deterministic, empirical and hybrid models, and the advantages and disadvantages of these approaches. It focuses on the low voltage (LV) PLC channel in both outdoor power distribution grids and in-home networks and dedicates to channel characterization of the medium voltage (MV) and the high voltage (HV) scenarios. The chapter discusses the characterization and modeling of multiple-input multiple-output (MIMO) PLC channels and presents the measurements and mathematical models for the noise experienced in PLC systems. It provides the main PLC channel characteristics in other scenarios, namely, the low voltage DC distribution grid scenario, the in-car scenario and the in-ship scenario.
2016
9781118676714
9781118676684
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11390/1267727
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