Analysis of Optimized Threshold with SLM based Blanking Non-Linearity for Impulsive Noise Reduction in Power Line Communication Systems

TL;DR

This paper demonstrates that applying Selective Mapping (SLM) to OFDM signals in power line communication systems enhances impulsive noise reduction by optimizing threshold settings, leading to significant SNR improvements and reduced computational complexity.

Contribution

The study introduces an optimized threshold method for blanking non-linearity in SLM-based OFDM, achieving maximum SNR gains and simplifying the noise reduction process.

Findings

Optimal threshold is constant for phase vectors ≥ 64 in SLM.

SNR gains up to 8.6dB with optimized threshold.

SLM reduces peak power and computational complexity.

Abstract

High amplitude impulsive noise (IN) occurrence over power line channels severely degrades the performance of Orthogonal Frequency Division Multiplexing (OFDM)systems. One of the simplest methods to reduce IN is to precede the OFDM demodulator with a blanking non-linearity processor. In this respect, Selective Mapping (SLM) applied to an OFDM signal before the transmitter does not only reduce Peak-to-Average Power Ratio (PAPR) but also increases the resulting Signal-to-Noise Ratio (SNR) when blanking nonlinearity is applied at the receiver. This paper highlights another advantage of SLM based IN reduction, which is the reduced dependency on threshold used for blanking nonlinearity. The simulation results show that the optimal threshold to achieve maximum SNR is found to be constant for phase vectors greater than or equal to 64 in the SLM scheme. If the optimized threshold calculation method is used, the output SNR with SLM OFDM will result in SNR gains of up to 8.6dB compared to the unmodified system, i.e. without implementing SLM. Moreover, by using SLM, we not only get the advantage of low peak power, but also the need to calculate optimized threshold is eliminated, thereby reducing the additional computation.