Impulsive noise blanking using quantized PAPR estimates in powerline communications

Impulsive noise (IN) is the most dominant factor degrading the performance of communication systems over powerlines. Many IN mitigation techniques have been introduced in the literature such as the application of a blanker at the frontend of the receiver which sets the incoming signal to zero when it exceeds a certain threshold. Determining this threshold is the key for achieving best performance in this technique. Most studies dealing with threshold optimization require prior knowledge about the IN characteristics. However, if the peak to average power ratio (PAPR) of the OFDM symbols can be determined at the receiver, this will allow optimal blanking of IN without requiring any knowledge about the noise parameters. In this paper we propose a look-up table (LUT) based algorithm with uniform quantization to estimate the peak of OFDM symbols. We also investigate the impact of quantization bits on the system performance in terms of the signal-to-noise-ratio (SNR) at the output of the blanking device, in two different scenarios, weakly and heavily disturbed IN environments. Simulation results reveal that a 5 bit LUT is sufficient for reliable performance.