Power line noise is known to affect the performance of broadband power-line communications significantly. This paper presents a frequency-domain approach to characterize and model the statistical variation of power-line noise. The model considers both the background noise and the impulsive noise. The background noise model is based on statistical analysis of the results from two long-term measurements of noise spectrum conducted at two separate sites of a laboratory and a residential apartment. On the other hand, the impulsive noise model is obtained by direct measurements from the noise sources (i.e., various electrical household appliances). The amount of impulse noise reaching a power-line communications (PLC) receiver can then be determined with consideration of the channel transfer characteristics between the noise sources and the PLC receiver. Using these noise models, the performance of two major classes of digital modulation schemes, namely single-carrier modulation and multicarrier modulation, are analyzed and compared. It is found that the multicarrier scheme performs better than the single-carrier scheme when subjected to the observed power-line noise with non-Gaussian statistics.Index Terms-Noise modeling, orthogonal frequency-division multiplexing (OFDM), performance study, power-line communications.

Summary A fundamental challenge for maintaining spatial orientation and interacting with the world is knowledge of our orientation relative to gravity, i.e. tilt. Sensing gravity is complicated because of Einstein’s equivalence principle, where gravitational and translational accelerations are physically indistinguishable. Theory has proposed that this ambiguity is solved by tracking head tilt through multisensory integration. Here we identify a group of Purkinje cells in the caudal cerebellar vermis with responses that reflect an estimate of head tilt. These tilt-selective cells are complementary to translation-selective Purkinje cells, such that their population activities sum to the net gravito-inertial acceleration encoded by the otolith organs, as predicted by theory. These findings reflect the remarkable ability of the cerebellum for neural computation and provide novel quantitative evidence for a neural representation of gravity, whose calculation relies on long-postulated theoretical concepts such as internal models and Bayesian priors.

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This paper presents a novel approach to model the transfer function of electrical power lines for broadband power line communication. In this approach, the power line is approximated as a transmission line and the two intrinsic parameters, the characteristic impedance and the propagation constants, are derived based on the lumped-element circuit model. Using these intrinsic parameters, the transfer characteristics for a N-branch power distribution network are derived based on the scattering matrix method. Detail derivation of this line model is given in this paper. The model has been verified with practical measurements conducted on actual power networks. It is demonstrated that the model accurately determine the line characteristics under different network configuration and when different household appliances are connected. Index Terms-Channel modeling, communication channel, power line communications.

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