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Quality of Service-Aware Resource Selection in Healthcare IoT Using Deep Autoencoder Neural Networks
Sastra University, Thanjavur, India.ORCID iD: 0000-0001-6116-2132
Galgotias University, Greater Noida, India; Instituto Federal De Educação, Ciência E Tecnologia Do Ceará, Fortaleza, Brazil.ORCID iD: 0000-0003-0094-0273
Universidade Federal Do Ceará, Fortaleza, Brazil.ORCID iD: 0000-0003-3886-4309
Halmstad University, School of Information Technology.ORCID iD: 0000-0002-2851-4260
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2022 (English)In: Human-centric Computing and Information Sciences, E-ISSN 2192-1962, Vol. 12, no 36, p. 1-16Article in journal (Refereed) Published
Abstract [en]

Heterogeneous network and device-to-device communication are two possible solutions for improving wireless network spectral efficiency. Techniques based on the Internet of Things (IoT) can interact between a large number of smart devices as well as heterogeneous networks. The goal of this study is to investigate proposed quality of service-aware resource selection in an IoT network for healthcare data using a deep auto encoder neural network with spectrum reuse utilizing mixed integer nonlinear programming (MINLP). The suggested MINLP spectrum reuse was used to address the optimization problem, and the spectrum allocation was done using fast Fourier transform based reinforcement Q-learning. Increased transmission repetitions have been identified as a promising strategy for improving IoT coverage by up to 164 dB in terms of maximum coupling loss for uplink transmissions, which is a significant improvement over traditional LTE technology, particularly for serving customers in deep coverage. Based on a comparison of existing methodologies, the experimental study is performed using parameters such as bit error rate of 40%, signal-to-interference plus noise ratio of 72%, sum rate of 88%, and spectral efficiency of 98% © 2022. Human-centric Computing and Information Sciences. All Rights Reserved.

Place, publisher, year, edition, pages
Heidelberg: Springer, 2022. Vol. 12, no 36, p. 1-16
Keywords [en]
D2d, Healthcare, Hetnet, Iot, Qos, Spectrum reuse
National Category
Telecommunications
Identifiers
URN: urn:nbn:se:hh:diva-48908DOI: 10.22967/HCIS.2022.12.036ISI: 000841211800001Scopus ID: 2-s2.0-85136087699OAI: oai:DiVA.org:hh-48908DiVA, id: diva2:1719398
Available from: 2022-12-15 Created: 2022-12-15 Last updated: 2023-03-09Bibliographically approved

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Tiwari, Prayag

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