Modeling Burst Error Processes in ITU-T G.hnem-Based PLC Systems: Noisy Indoor Environment Analysis Using a Generative Semi-Hidden Markov Model

Power line communication (PLC) systems are essential for modern telecommunications, providing a cost-effective solution for data transmission over existing electrical wiring. However, indoor environments pose significant challenges for these systems, primarily due to burst errors caused by impulsive...

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Main Authors: Akintunde Oluremi Iyiola, Theo G. Swart, Ayokunle Damilola Familua, Thokozani Shongwe
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
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Online Access:https://ieeexplore.ieee.org/document/10845759/
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author Akintunde Oluremi Iyiola
Theo G. Swart
Ayokunle Damilola Familua
Thokozani Shongwe
author_facet Akintunde Oluremi Iyiola
Theo G. Swart
Ayokunle Damilola Familua
Thokozani Shongwe
author_sort Akintunde Oluremi Iyiola
collection DOAJ
description Power line communication (PLC) systems are essential for modern telecommunications, providing a cost-effective solution for data transmission over existing electrical wiring. However, indoor environments pose significant challenges for these systems, primarily due to burst errors caused by impulsive noise, narrowband interference, and signal attenuation. This study seeks to address these challenges by utilizing three-state Semi-Hidden Markov Models (SHMMs) to analyze and characterize burst error processes in narrowband PLC (NB-PLC) systems. We developed a software-defined multi-state quadrature amplitude modulation (M-QAM) orthogonal frequency division multiplexing (OFDM)-based NB-PLC testbed that adheres to the International Telecommunication Union - Telecommunication Standardization Sector (ITU-T) G.hnem standard for home networking over existing wiring, such as power lines, phone lines, and coaxial cables. The system incorporates 4-QAM-OFDM, 8-QAM-OFDM, and 16-QAM-OFDM modulation schemes, utilizing Universal Software Radio Peripheral (USRP) hardware for real-time transmission and reception. Using this experimental setup, we generated and analyzed a dataset of 200,000 transmitted bits, capturing the characteristics of burst errors under realistic indoor noise conditions. A comparative analysis of reference error sequences and SHMM simulations demonstrates the model’s ability to accurately replicate NB-PLC-specific error dynamics, including error clustering and state transitions. This research makes four key contributions: (1) the development of a robust experimental testbed for real-time burst error analysis in NB-PLC systems, (2) the creation of a comprehensive dataset that characterizes noise-induced disruptions in real-world indoor scenarios, (3) a theoretical exploration and practical application of SHMMs for modeling error sequences in NB-PLC channels, and (4) the validation of SHMMs and a modified Baum-Welch algorithm (BWA) for efficient modeling and parameter estimation of burst error processes. Together, these contributions enhance the understanding of burst error dynamics and provide a foundation for improving the resilience and efficiency of NB-PLC networks in real-world indoor environments.
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spelling doaj-art-f8c9e38258214cb484f9f7dd70be8d562025-01-31T00:00:42ZengIEEEIEEE Access2169-35362025-01-0113167331675110.1109/ACCESS.2025.353181710845759Modeling Burst Error Processes in ITU-T G.hnem-Based PLC Systems: Noisy Indoor Environment Analysis Using a Generative Semi-Hidden Markov ModelAkintunde Oluremi Iyiola0https://orcid.org/0000-0002-6371-7805Theo G. Swart1https://orcid.org/0000-0002-1525-7728Ayokunle Damilola Familua2https://orcid.org/0000-0003-1715-5503Thokozani Shongwe3https://orcid.org/0000-0002-3011-7600Department of Electrical and Electronic Engineering Science, University of Johannesburg, Johannesburg, South AfricaDepartment of Electrical and Electronic Engineering Science, University of Johannesburg, Johannesburg, South AfricaDepartment of Electrical and Electronic Engineering Science, University of Johannesburg, Johannesburg, South AfricaDepartment of Electrical and Electronic Engineering Technology, University of Johannesburg, Johannesburg, South AfricaPower line communication (PLC) systems are essential for modern telecommunications, providing a cost-effective solution for data transmission over existing electrical wiring. However, indoor environments pose significant challenges for these systems, primarily due to burst errors caused by impulsive noise, narrowband interference, and signal attenuation. This study seeks to address these challenges by utilizing three-state Semi-Hidden Markov Models (SHMMs) to analyze and characterize burst error processes in narrowband PLC (NB-PLC) systems. We developed a software-defined multi-state quadrature amplitude modulation (M-QAM) orthogonal frequency division multiplexing (OFDM)-based NB-PLC testbed that adheres to the International Telecommunication Union - Telecommunication Standardization Sector (ITU-T) G.hnem standard for home networking over existing wiring, such as power lines, phone lines, and coaxial cables. The system incorporates 4-QAM-OFDM, 8-QAM-OFDM, and 16-QAM-OFDM modulation schemes, utilizing Universal Software Radio Peripheral (USRP) hardware for real-time transmission and reception. Using this experimental setup, we generated and analyzed a dataset of 200,000 transmitted bits, capturing the characteristics of burst errors under realistic indoor noise conditions. A comparative analysis of reference error sequences and SHMM simulations demonstrates the model’s ability to accurately replicate NB-PLC-specific error dynamics, including error clustering and state transitions. This research makes four key contributions: (1) the development of a robust experimental testbed for real-time burst error analysis in NB-PLC systems, (2) the creation of a comprehensive dataset that characterizes noise-induced disruptions in real-world indoor scenarios, (3) a theoretical exploration and practical application of SHMMs for modeling error sequences in NB-PLC channels, and (4) the validation of SHMMs and a modified Baum-Welch algorithm (BWA) for efficient modeling and parameter estimation of burst error processes. Together, these contributions enhance the understanding of burst error dynamics and provide a foundation for improving the resilience and efficiency of NB-PLC networks in real-world indoor environments.https://ieeexplore.ieee.org/document/10845759/Burst errorG.hnem standardMarkov modelsnarrowband power line communication (NB-PLC)orthogonal frequency-division multiplexing (OFDM)semi-hidden Markov model (SHMM)
spellingShingle Akintunde Oluremi Iyiola
Theo G. Swart
Ayokunle Damilola Familua
Thokozani Shongwe
Modeling Burst Error Processes in ITU-T G.hnem-Based PLC Systems: Noisy Indoor Environment Analysis Using a Generative Semi-Hidden Markov Model
IEEE Access
Burst error
G.hnem standard
Markov models
narrowband power line communication (NB-PLC)
orthogonal frequency-division multiplexing (OFDM)
semi-hidden Markov model (SHMM)
title Modeling Burst Error Processes in ITU-T G.hnem-Based PLC Systems: Noisy Indoor Environment Analysis Using a Generative Semi-Hidden Markov Model
title_full Modeling Burst Error Processes in ITU-T G.hnem-Based PLC Systems: Noisy Indoor Environment Analysis Using a Generative Semi-Hidden Markov Model
title_fullStr Modeling Burst Error Processes in ITU-T G.hnem-Based PLC Systems: Noisy Indoor Environment Analysis Using a Generative Semi-Hidden Markov Model
title_full_unstemmed Modeling Burst Error Processes in ITU-T G.hnem-Based PLC Systems: Noisy Indoor Environment Analysis Using a Generative Semi-Hidden Markov Model
title_short Modeling Burst Error Processes in ITU-T G.hnem-Based PLC Systems: Noisy Indoor Environment Analysis Using a Generative Semi-Hidden Markov Model
title_sort modeling burst error processes in itu t g hnem based plc systems noisy indoor environment analysis using a generative semi hidden markov model
topic Burst error
G.hnem standard
Markov models
narrowband power line communication (NB-PLC)
orthogonal frequency-division multiplexing (OFDM)
semi-hidden Markov model (SHMM)
url https://ieeexplore.ieee.org/document/10845759/
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