Study on modified curve fitting model in analyzing YIG resonator antenna

Othman, Mohamadariff; Ali, Wan Fahmin Faiz Wan; Ain, Mohd Fadzil; Ahmad, Zainal Arifin; Mahiyiddin, Wan Amirul Wan Mohd; Qasaymeh, Yazeed

doi:10.1002/mop.31570

Cited by 2 publications

(2 citation statements)

References 11 publications

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“…A rising number of people are interested in using machine learning (ML) techniques to create data-driven, adaptive sleep scheduling algorithms for NB-IoT networks in order to get around these limits. [3,4]…”

Section: Introductionmentioning

confidence: 99%

Optimizing Energy-Conserving Sleep Strategies for NB-IoT Devices in Coordinated 5G Networks within Smart Environments

Jenitha,

Hema,

Regilan

2024

Preprint

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An increased interest in energy-efficient communication protocols to extend battery life and improve network scalability has resulted from the fast growth of Internet of Things (IoT) devices, especially Narrowband IoT (NB-IoT) devices. In this study, we suggest a unique method of sleep scheduling using machine learning techniques for NB-IoT networks. Our method seeks to optimize energy usage while maintaining responsive connection by dynamically adjusting the sleep patterns of NB-IoT devices depending on anticipated network activity levels. Using machine learning algorithms trained on historical data gathered from NB-IoT devices and base stations, the suggested process entails developing a prediction model. In order to produce real-time estimates of future network demand, the model analyzes a variety of input parameters, including as the surrounding environment, traffic patterns, and the closeness of the device to the base station. The sleep scheduling mechanism, which coordinates the sleep-wake cycles of NB-IoT devices to coincide with expected periods of low activity, is informed by these forecasts. We illustrate the efficacy of our machine learning-based sleep scheduling technique in attaining noteworthy energy savings while maintaining network performance, utilizing comprehensive simulations and real-world tests. We are able to strike a compromise between energy economy and responsiveness by cleverly scheduling sleep, which keeps NB-IoT devices operational for their monitoring and control functions while preserving battery life. Our study addresses the increasing need for sustainable IoT solutions in smart city settings and beyond by advancing energy-efficient communication protocols for NB-IoT networks. The suggested method opens the door for more effective and durable IoT ecosystems by providing useful advice and insights for applying machine learning-based sleep scheduling algorithms in actual IoT installations.

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Section: Introductionmentioning

confidence: 99%

Optimizing Energy-Conserving Sleep Strategies for NB-IoT Devices in Coordinated 5G Networks within Smart Environments

Jenitha,

Hema,

Regilan

2024

Preprint

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“…One of the advantages of the YIG compound used is to be a ferrite with permeability greater than one, compared to those in the literature 9‐11 . Additionally, it has low losses, compared to References 10 and 11.…”

Section: Introductionmentioning

confidence: 99%

Dual‐frequency magneto‐dielectric resonator antenna based in a YIG matrix with control of HEM_11δ and TE_01δ modes

Costa

Fontgalland

Neto³

et al. 2020

Micro & Optical Tech Letters

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This work presents a magneto-dielectric cylindrical resonator antenna (MDCRA) based on the YIG matrix, presenting two relevant new features. The first feature is to allow independent control of modes and the second one a dual-band response. The MDCRA has two distinct propagation modes HEM 11δ (5.78 GHz) and TE 01δ (6.75 GHz) which can be controlled independently. The magneto-dielectric resonator is manufactured using the magnetic ceramic material originated from the ferrites (Yttrium Iron Garnet, YIG) of composition Y 3 Fe 2 (FeO 4) 3 , which is placed on low cost FR4 dielectric substrate. The microstrip feeding mechanism design assures the decoupling of the two modes by using orthogonal microstrip lines. The proposed MDCRA antenna was designed, fabricated, and then characterized inside an anechoic chamber. The scattering S-parameters were analyzed in the frequency bands from 4.9 GHz to 7.6 GHz, with results within the expected range. The 2-D and 3-D radiation patterns are also presented. The validation was carried out with analytical mathematical equations, numerical formulation using the commercial CST Studio software, and experimental results, which shows a good agreement.

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Study on modified curve fitting model in analyzing YIG resonator antenna

Cited by 2 publications

References 11 publications

Optimizing Energy-Conserving Sleep Strategies for NB-IoT Devices in Coordinated 5G Networks within Smart Environments

Optimizing Energy-Conserving Sleep Strategies for NB-IoT Devices in Coordinated 5G Networks within Smart Environments

Dual‐frequency magneto‐dielectric resonator antenna based in a YIG matrix with control of HEM_11δ and TE_01δ modes

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Study on modified curve fitting model in analyzing YIG resonator antenna

Cited by 2 publications

References 11 publications

Optimizing Energy-Conserving Sleep Strategies for NB-IoT Devices in Coordinated 5G Networks within Smart Environments

Optimizing Energy-Conserving Sleep Strategies for NB-IoT Devices in Coordinated 5G Networks within Smart Environments

Dual‐frequency magneto‐dielectric resonator antenna based in a YIG matrix with control of HEM11δ and TE01δ modes

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Dual‐frequency magneto‐dielectric resonator antenna based in a YIG matrix with control of HEM_11δ and TE_01δ modes