Meta-material Sensors based Internet of Things for 6G Communications

Hu, Jingzhi; Zhang, Hongliang; Di, Boya; Bian, Kaigui; Song, Lingyang

doi:10.1109/globecom46510.2021.9685846

Cited by 3 publications

(2 citation statements)

References 12 publications

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“…This lays the foundation for the proposed system to detect humidity and temperature anomalies. Furthermore, the results of the analytical reflection coefficient model in (20) are in accordance with the results of the full-wave simulation in different cases, which verifies the effectiveness of the analytical model. ?+#@#+<9#"(#A( E,$@,+%<8+,(!…”

Section: Discussionsupporting

confidence: 71%

“…In [18], the authors proposed to sense temperature with an array of meta-material-based wireless sensors, and demonstrated the feasibility of wireless temperature sensing up to 200 • C. In [19], the authors designed a meta-material-based sensor to sense humidity and methanol-deionized water solutions inside a waveguide testbed. In [20][21],…”

Section: B Meta-meterial Sensor Based Systemsmentioning

confidence: 99%

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Meta-Material Sensor Based Internet of Things: Design, Optimization, and Implementation

Hu¹,

Zhang²,

Di³

et al. 2022

IEEE Trans. Commun.

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For many applications envisioned for the Internet of Things (IoT), it is expected that the sensors will have very low costs and zero power, which can be satisfied by meta-material sensor based IoT, i.e., meta-IoT. As their constituent meta-materials can reflect wireless signals with environment-sensitive reflection coefficients, meta-IoT sensors can achieve simultaneous sensing and transmission without any active modulation. However, to maximize the sensing accuracy, the structures of meta-IoT sensors need to be optimized considering their joint influence on sensing and transmission, which is challenging due to the high computational complexity in evaluating the influence, especially given a large number of sensors. In this paper, we propose a joint sensing and transmission design method for meta-IoT systems with a large number of meta-IoT sensors, which can efficiently optimize the sensing accuracy of the system. Specifically, a computationally efficient received signal model is established to evaluate the joint influence of meta-material structure on sensing and transmission. Then, a sensing algorithm based on deep unsupervised learning is designed to obtain accurate sensing results in a robust manner.Experiments with a prototype verify that the system has a higher sensitivity and a longer transmission range compared to existing designs, and can sense environmental anomalies correctly within 2 meters.

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Section: Discussionsupporting

confidence: 71%

Section: B Meta-meterial Sensor Based Systemsmentioning

confidence: 99%

Meta-Material Sensor Based Internet of Things: Design, Optimization, and Implementation

Hu¹,

Zhang²,

Di³

et al. 2022

IEEE Trans. Commun.

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Meta-IoT: Simultaneous Sensing and Transmission by Meta-Material Sensor-Based Internet of Things

Zhang

et al. 2022

IEEE Trans. Wireless Commun.

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6G-Enabled Internet of Things: Vision, Techniques, and Open Issues

Hosseinzadeh¹,

Hemmati²,

Rahmani³

2022

Computer Modeling in Engineering &Amp; Sciences

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There are changes in the development of wireless technology systems every decade. 6G (sixth generation) wireless networks improve on previous generations by increasing dependability, accelerating networks, increasing available bandwidth, decreasing latency, and increasing data transmission speed to standardize communication signals. The purpose of this article is to comprehend the current directions in 6G studies and their relationship to the Internet of Things (IoT). Also, this paper discusses the impacts of 6G on IoT, critical requirements and trends for 6G-enabled IoT, new service classes of 6G and IoT technologies, and current 6G-enabled IoT studies selected by the systematic literature review (SLR) method published from 2018 to 2021. In addition, we present a technical taxonomy for the classification of 6G-enabled IoT, which includes self-organization systems, energy efficiency, channel assessment, and security. Also, according to the articles reviewed, we consider the evaluation factors in this domain, including data transmission, delay, energy consumption, and bandwidth. Finally, we focus on open issues and future research challenges in 6G-enabled IoT. To mention important future challenges and directions, we can point to

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Meta-material Sensors based Internet of Things for 6G Communications

Cited by 3 publications

References 12 publications

Meta-Material Sensor Based Internet of Things: Design, Optimization, and Implementation

Meta-Material Sensor Based Internet of Things: Design, Optimization, and Implementation

Meta-IoT: Simultaneous Sensing and Transmission by Meta-Material Sensor-Based Internet of Things

6G-Enabled Internet of Things: Vision, Techniques, and Open Issues

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