Quantized Peak-Based Impulsive Noise Blanking in Power-Line Communications

Impulsive-noise (IN) over power-line channels can cause serious performance degradations. As such, many IN mitigation techniques have been proposed in the literature, 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, we propose a lookup table (LUT)-based algorithm with uniform quantization to utilize estimates of the peak-to-average power ratio at the receiver to determine the OBT. To fully evaluate the performance of the proposed method, we investigate the impact of quantization bits on the system performance in terms of 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 3-dB SNR improvement relative to the conventional blanking method. It will also be shown that to maintain good performance, the resolution of quantization must be increased especially when the IN probability of occurrence is relatively high.