###### Abstract  
Within the power line communication (PLC) network, a large number of electronic devices are connected, and environmental factors can cause unusual behavior, leading to high-amplitude impulse noise in the received signal and, as a result, packet losses and burst errors in the data that are sent. Burst errors make it difficult to send data over power line channels efficiently and accurately. Analyzing error patterns with intelligent techniques can provide valuable insights into data transmission efficiency, enhance transmission quality, and optimize PLC systems. This research proposes a three-state Fitchman-Markov chain-based power line communication error model and develops a software-defined PLC system. The goal is to analyze and model the system's statistical error process. The PLC system's fundamental error pattern is deduced from the transmission and reception of data on our software-defined (SD) PLC platform. The system is designed with multi-state quadrature amplitude modulation (M-QAM) data transmission and reception techniques. An error pattern consisting of 50,000 bits is obtained by comparing the bits transmitted with those received using the in-house M-QAM-based PLC transceiver system. The error characteristics of the newly developed M-QAM SD-PLC system are precisely modeled using the error model. Examining the burst error statistics of the reference error sequences of the SD-PLC system and the three-state Fitchman-Markov error model reveals striking similarities. According to the results, the error model accurately represents the error characteristics of the developed M-QAM SD-PLC system. The proposed three-state Fitchman-Markov chain-based error model for PLC has the potential to provide a comprehensive understanding of the error process in PLC. Additionally, it can assess error control strategies with less computational complexity and a shorter simulation time. error sequence; Fitchman-Markov model; impulse noise error; power line communication; quadrature amplitude modulation; software-defined radio 2023  
2023/10/18/2023/10/08/10/1  
The main impairment affecting PLC systems' reliability is the additive power line noise [7; 8; 9; 10]. This noise is generated by electrical devices connected to power lines, external noise, and interference coupled to the power lines through radiation or conduction [11]. The PLC channel noise can be divided into several categories based on the source, level, and physical characteristics. According to [7], noise in PLC channels can be classified as colored background noise, periodic impulsive noise synchronous with the mains, periodic asynchronous impulsive noise, aperiodic impulse noise, and narrow-band interference from both internal and external sources. Comprehensive information on the sources and effects of these noise types on reliable data transmission on the PLC channel can be found in [10; 12]. For modeling flexibility, these five types of noise found in PLC are typically divided into two primary categories: background noise and impulsive noise. Impulse noise is the most challenging type of noise to deal with in PLC systems, and it is the primary cause of data transmission errors when communicating via an indoor power line channel [12; 13; 14]. In-house power line communication (PLC) systems can be affected by impulse noise, which can introduce disturbances and interfere with the transmission of data signals over the power line network. Unlike background noise, which is stationary, impulse noise occurs at short intervals but has a high power spectral density (PSD) that is up to 40 dB higher than that of background noise [15]. Impulse noise is a type of non-stationary stochastic electromagnetic interference, with random spikes in signal strength and changing spectral content.