A Comparison of ICF and Companding for Impulsive Noise Mitigation in Powerline Communication Systems

In future smart cities, smart grid technologies which are usually enabled by Powerline Communication (PLC) techniques are required. However, data transmission over powerline channel traverses a non-Gaussian media due to the presence of Impulsive Noise (IN) operating at the frequencies of PLC system which can be deployed using the IEEE 1901, that uses Orthogonal Frequency Division Multiplexing (OFDM). These OFDM signals have asymmetric amplitude distribution, which makes it difficult to identify and mitigate the IN presence. Converting the amplitude distribution to a uniform distribution can enhance the ability to mitigate IN when nonlinear IN mitigation techniques such as blanking is applied. In this study, we apply Iterative Clipping and Filtering (ICF) and companding schemes which are Peak-to-Average Power Ratio (PAPR) reduction techniques to enable symmetric amplitude distribution of the OFDM signals. With an optimization search for the optimal blanking amplitude for the two PAPR reduction schemes. Results show that companding scheme achieves 4dB gain in terms of received signal-to-noise ratio better than ICF after the blanking was used to remove the IN

A new Approach to Iterative Clipping and Filtering PAPR Reduction Scheme for OFDM Systems

While achieving reduced/good peak-to-average power (PAPR) in orthogonal frequency division multiplexing (OFDM) systems is attractive, this must not be performed at the expense of the transmitted signal with over-reduced signal power as it leads to degraded bit error ratio (BER). We introduce a uniform distribution approach to solving the PAPR reduction problem of OFDM signals and then use Lagrange multiplier (LM) optimization to minimize the number of iterations involved in an adaptive fashion. Due to the nonlinear attenuation of the PAPR reduction scheme, we compensate the output signal using a correlation factor that minimizes the error floor in the in-band distortion of the clipped signal using minimum mean square error (MMSE) method so as to improve the BER performance. Three different methods are introduced each enabling PAPR reduction by clipping followed by filtering with no direct dependency on a clipping ratio parameter. We find that our approach significantly reduces the PAPR of the OFDM signals (especially with LM optimization) better than the conventional adaptive iterative clipping and filtering operating without LM optimization. Based on our proposed methods, we additionally outline two simple steps for achieving perfect PAPR reduction (i.e. 0dB). We also evaluate the performance of the three new models over high power amplifier (HPA) for completeness; the HPA is found to induce negligible BER degradation effects on the processed signal compared to the unprocessed signal