To satisfy the smart grid electrical network, communication systems in high-voltage substations have to be installed in order to control equipments. Considering that those substations were not necessarily designed for adding communication networks, one of the most appropriate solutions is to use wireless sensor network (WSN). However, the high voltage transported through the station generates a strong and specific radio noise. In order to prepare for such a network, the electromagnetic environment has to be characterized and tests in laboratories have to be performed to estimate the communication performances. This paper presents a method for measuring the noise due to high voltage and more particularly the impulsive noise. In the laboratory, we generate the impulsive noise using two specimens, and we show that these laboratory measurements validate the field measurements of Pakala et al. For the two specimens, it aims to link the noise characteristics (magnitude and frequency) with the specimen parameters (power supply and geometric dimensions) to predict the environments where wireless communications can be troublesome. By using different sets of this measured noise, we show that the statistical model of Middleton Class A can be used to model the impulsive noise in high-voltage substations better than the Gaussian model. We consider a cooperative multiple-input-multiple-output (MIMO) system to achieve the wireless sensor communication. This system uses recent MIMO techniques based on precoding like max-d min and P-OSM precoders. The MIMO precoder-based cooperative system is a potential candidate for energy saving in WSN since energy efficiency optimization is a very important critical issue. Since MIMO precoders are with Gaussian noise assumption, we evaluate the performance of several MIMO precoders in the presence of impulsive noise using estimated parameters from the measured noise.
International audiencePrecoders permits to enhance the performance of MIMO systems by optimizing a pertinent criterion of the transmission. For example, the max-dmin precoder optimizes the minimum Euclidean distance of the received constellation. In this paper, we evaluate the performance of max-dmin in a realistic time-variant channel for both spectral efficiency (4 and 8 bit/s/Hz). The channel is obtained by a 3D Propagation Simulation Software based on a raytracing method. Moreover, the speed effect is introduced by using the Jakes' model. We are able to obtain the temporal evolution of the channel and the statistics of key random variables. This permits us to study the max-dmin precoder with a perfect channel state information and with a simple channel error estimation. The max-dmin is also compared to the max-SNR precoder
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