Difference sets-based compressive sensing as denoising method for narrow-band power line communications

The present work analyses and compares two of the most popular specifications for data transmission over power line networks: PoweRline Intelligent Metering Evolution (PRIME) and G3-power line communication (G3-PLC). A simulation model has been built using Matlab software in order to evaluate their respective performances with special focus on impulsive noise environments. For this purpose, Middleton´s Class-A noise model was used in conjunction with measured noise parameters reported in the literature for the narrow-band spectrum. The performance is measured in terms of bit error rate versus signal to noise ratio. Simulation results show how G3-PLC outperforms PRIME when the channel is impaired by such type of noise. Moreover, although the use of compressive sensing to cancel impulsive noise in communications has already been proposed in other studies, this paper details a modification based on Partial Fourier Matrix indexing according to difference sets. Results from simulations report an almost complete cancellation of the impulsive noise effects. An advantage of this technique is that no redundancy is added to the message; therefore no decrement in the transmission rate is experienced.