In the [1.8-30] MHz frequency band, EMC standards prohibit power line communications (PLC) to emit on the frequencies which could be used by HAM radio in order to protect them. This implies an transmit power restriction in these radio frequencies and consequently a throughput limitation. With the aim to increase the data rates, the solutions envisaged today consist in limiting the number of notched frequencies as well as in increasing the used frequency band, which can henceforth overlap with the FM band [87.5-108] MHz for future PLC systems. With the current static notching solution, the whole frequencies of the FM band can be notched during PLC transmission. As in a given environment and at a given time, only a part of the FM radio frequencies are really received, a cognitive EMC approach is proposed in this paper. The power line network is demonstrated to be a good antenna that can detect all present radio frequencies and a cognitive detection method is proposed. By means of simulations, it is also shown that the use the cognitive technique improves the data rates of the PLC systems.
The electrical appliances shared with PLC modems in the same powerline network generate noises. Among them, impulsive noises are the main source of interference resulting in signal distortions and bit errors during data transmission. Many impulsive noise models were proposed in the literature. They share the same impulsive noise definition: "unpredictable noises measured at the receiver side". This definition leads to the modelling of thousands of impulsive noises whose plurality would very likely come from the diversity of paths that the original impulsive noise took. In this paper, an innovative modelling approach is applied to impulsive noises which are henceforth studied directly at their sources. Noise at the receiver is considered as the noise model at the source filtered by the powerline channel. Effective in-device sources of impulsive noises are identified and classified into six classes, from which representative noises are proposed. Based on impulsive modelling at source, a receiver side model is finally proposed.
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