Impulsive Noise Detection and Mitigation in OFDM-based Power-Line Communications

Smart grid can be a solution for reducing greenhouse gas (GHG) emissions. To perform its task, smart grid needs a communication link to communicate between nodes or devices. Using power-line communications (PLC) is beneficial as the power-lines infrastructure has been available. However, in PLC the transmitted signal undergoes multipath channels and impulsive noise corruption. Meanwhile, orthogonal frequency-division multiplexing (OFDM) is the well-known modulation used in PLC. Although OFDM is able to spread the energy of the impulsive noise, it still degrades the system performance. Therefore, detecting and mitigating the impulsive noise are required to improve the reliability of the OFDM-based PLC. This thesis focuses on impulsive noise mitigation methods in the broadband PLC systems. First, a generic nonlinear preprocessor, which is called deep clipping, is presented. Deep clipping is characterised by two parameters, namely, threshold and depth factor. The expression for the output signal-to-noise ratio (SNR) of the deep clipping is derived. By optimising the parameters, it can be found that the performance of deep clipping outperforms the other nonlinear preprocessors, such as blanking, conventional clipping, and joint blanking/clipping. In addition, it can be found that by setting the two parameters of the deep clipping properly, the expressions for other nonlinear preprocessors can be obtained. Next, a linear combination of nonlinear preprocessors is proposed to further improve the performance of the OFDM-based PLC. The combination of blanking and conventional clipping and the combination of conventional clipping and joint blanking/clipping are analysed. The output SNR mathematical expressions for both combinations are also derived. The simulation results show that the output SNR of the linear combination method outperforms the output SNR of the individual method. Then, as OFDM systems suffer from high peak-to-average power ratio (PAPR), the nonlinear preprocessor can falsely detect the impulsive noise. As a result, if the PAPR is reduced, the performance of the system is improved. The use of Guel’s clipping method as a PAPR reduction method is proposed as this clipping method does not impact the bit error rate (BER) performance. From the simulation results, it can be seen that our proposed method improves the BER performance of OFDM-based PLC over impulsive noise channel. Finally, considering that impulsive noise is sparse and OFDM systems usually employ null subcarriers, the smoothed l0-norm method is proposed to detect impulsive noise. The proposed method is compared with the conventional l1-norm detection. The simulation results show that the proposed method has lower complexity than that of the conventional l1-norm while having better (or sometimes the same) performance.