Quantized Peak Based Impulsive Noise Blanking in Powerline Communications

Many IN mitigation techniques have been proposed to mitigate impulsive noise (IN) over powerlines, the most common of which is the blanking technique. The conventional way to implement this technique however requires prior knowledge about the IN characteristics to identify the optimal blanking threshold (OBT). When such knowledge cannot be obtained the performance deteriorates rapidly. To alleviate this, a look-up table (LUT) based algorithm with uniform quantization is deployed to utilize estimates of the peak to average power ratio at the receiver to determine the OBT. In this paper, we investigate the impact of quantization bits on the system performance as well as the performance loss due to the impact of IN on the side information. Two aspects of the achievable performance are considered namely, output signal-to-noise ratio (SNR) and symbol error rate under various IN scenarios. The results reveal that a 5 bit LUT is sufficient to achieve a gain of up to 3dB SNR improvement relative to the conventional blanking method. Furthermore, it will be shown that the loss due to the practical impact of IN on the side information is insignificant.