RESUMEN
This paper deals with fault detection and isolation (FDI) in complex embedded wired communication networks. The considered faults are soft faults which do not prevent the communication, but may evolve into hard faults, i.e. short or open circuit. A novel FDI method based on power line communication (PLC) transmission systems is proposed. In these PLC systems, the transmission coefficients between the source and each receiver are estimated for communication purposes using orthogonal frequency division multiplexing (OFDM). Health indicators and residuals are computed by comparing the online estimated transmission coefficients with the reference coefficients. A methodology for dealing with complex networks, such as bus networks, is proposed. It is based on the decomposition of the network into several Y-shaped sub-networks. Each of these sub-networks is monitored to detect the presence of a fault. The FDI method is first validated using real data extracted from a Y-shaped network test bench. Then, the proposed approach is validated on a more complex network using realistic simulated data.
RESUMEN
Massive multiple-input multiple-output (mMIMO) communication systems are a pillar technology for 5G. However, the wireless radio channel models relying on the assumption of wide-sense stationary uncorrelated scattering (WSSUS) may not always be valid for dynamic scenarios. Nonetheless, an analysis of the stationarity time that validates this hypothesis for mMIMO vehicular channels as well as a clear relationship with the scattering properties is missing in the literature. Here, time-varying single-user mMIMO radio channels were measured in a suburban environment at the 5.89 GHz vehicular band with a strong Line-of-Sight (LOS) to study the non-WSSUS and large scale characteristics of the vehicle-to-infrastructure (V2I) link. The generalized local scattering function (GLSF), computed from the sampled channels, was used to derive (1) the spatial distribution of the stationarity time using the channel correlation function (CCF) and empirical collinearity methods and (2) the root mean square delay/angular spread and coherence time/bandwidth values from the projected power delay profile (PDP) and Doppler power spectra (DPS). The results highlight the high degree of correlation between the spatial distribution of the stationarity time and the scattering properties along the measurement route.