# Mdpi
## 1 Introduction  
With an advanced metering infrastructure (AMI), researchers have shown that broadband powerline communication (BB-PLC) systems are applicable to backhaul communication [1] and service quality estimation [2]. In Korea, a power company has adopted BB-PLC systems for nationwide AMI to serve 22.50 million low-voltage customers until 2020 [2]. For distributed smart grid applications, BB-PLC systems are possible wired technologies to indoor communications between smart meters and photovoltaic inverters [3]. One of the advantages of powerline communication (PLC) technologies is that the powerline infrastructure has already deployed so that installation costs could be reduced. The transmission distance for BB-PLC is up to about 1.5 kilometers, it is more suitable for home area networks [4] (p. 117). Some field trials have been conducted to validate feasibility of using BB-PLC for smart grid applications [5]. It has pointed out that narrowband PLC (NB-PLC) is affected by inverters used in some home appliances. This is mainly because of NB-PLC and inverters are operating on the same frequency band (3-148.5 kHz). However, BB-PLC does not suffer from such problems because ofusing a broad frequency band (3-30 MHz). In addition, the highest available date rate with NB-PLC, which is around 500 Kb/s, is insufficient for common and future smart grid services. However, PLC was designed for power delivery rather than data transmission; therefore, from the perspective of data transmission, issues associated with PLC channels like impulsive noise (IN), frequency-dependent attenuation, narrowband interference, and time-varying impedance are needed to be addressed [6; 7]. The most intractable issue is IN. Due to the short duration and high magnitude properties, IN can be regarded as high-power wideband noise in the frequency domain [8]. In PLC systems based on orthogonal frequency-division multiplexing (OFDM), the noise bucket effect [9] significantly increases in the bit error rate (BER) [10]. BB-PLC schemes with two physical specifications have been proposed by IEEE: fast Fourier transform (FFT) -based OFDM and wavelet-based OFDM [11]. Wavelet-OFDM-based PLC employs an \(M\)-band transmultiplexer, which allows the stopband attenuation of subcarriers to exceed 35 dB [12]. Comparing with FFT-based OFDM systems, wavelet-based OFDM systems offer better subchannel isolation. An inverse discrete wavelet transform (IDWT) block is used at the transmitter and a discrete wavelet transform (DWT) block is used at the receiver. Many IN mitigation schemes have been proposed for FFT-OFDM-based PLC systems. [PERSON] assessed a number of nonlinear IN mitigation techniques, included clipping, nulling, and a mixture of both nulling and clipping approaches [13]. A scheme combining nulling, clipping, and replacement was proposed in Reference [14], and the multipath issue was further considered in Reference [15]. A scheme based on deep clipping was proposed in Reference [16] to enhance the effectiveness of the nonlinear IN mitigation methods described above. Unfortunately, some pre-determined parameters, which tend to vary with the channel conditions, are required for determining the threshold values. In Reference [17], the authors utilized zero carriers to estimate noise power and the IN parameters were extracted to calculate the optimal clipping threshold. However, [PERSON] pointed out that nonlinear devices used to mitigate IN cause intercarrier interference and degrade system performance [18]. Consequently, [PERSON] reported an iterative IN mitigation scheme for OFDM-based digital terrestrial video broadcasting systems [19]. A number of sophisticated multilayer perceptron [20] and deep neural network [21] schemes have been developed to mitigate IN. An iterative receiver for FFT-OFDM-based PLC systems was proposed in Reference [22], which simultaneously considered the channel estimation, channel equalization, and IN mitigation issues in the frequency domain.