Performance analysis on the low-power energy harvesting wireless sensor networks with a novel relay selection scheme

Simultaneous wireless information and power transfer (SWIPT) has been utilized widely in wireless sensor networks (WSNs) to design systems that can sustain themselves by harvesting energy from the surrounding areas. In this study, we investigated the performance of the so-called low-power energy har...

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Detalles Bibliográficos
Autores: NGUYEN, Hoang-Sy, Van, Hoang-Phuong
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2023
País:México
Institución:UNIVERSIDAD NACIONAL AUTÓNOMA DE MÉXICO
Repositorio:Journal of Applied Research and Technology
Idioma:inglés
OAI Identifier:oai:ojs2.localhost:article/1846
Acceso en línea:https://jart.icat.unam.mx/index.php/jart/article/view/1846
Access Level:acceso abierto
Palabra clave:Wireless sensor network
Low-Power network
Relay selection
Markov model
Outage probability
Log-normal fading
Descripción
Sumario:Simultaneous wireless information and power transfer (SWIPT) has been utilized widely in wireless sensor networks (WSNs) to design systems that can sustain themselves by harvesting energy from the surrounding areas. In this study, we investigated the performance of the so-called low-power energy harvesting (LPEH) WSN. Being different from other studies, we equipped each relay with a battery whose characteristics were described by an on/off (1/0) decision scheme as per the Markov property. In this context, an optimal loop interference relay selection (OPLIRS) was proposed and investigated. Moreover, the crucial role of the log-normal distribution method in characterizing the LPEH WSN’s constraints was proven and emphasized. The system performance was evaluated in terms of the overall ergodic outage probability (OP) both analytically and numerically with Monte Carlo simulation. Readers can refer to this paper for guidelines on defining the networks’ constraints, analytically derivating the problems, or use the presented results for possible comparison studies.