Coexistence of Wi-Fi and IoT Communications in WLANs

Pirayesh, Hossein; Sangdeh, Pedram Kheirkhah; Zeng, Huacheng

doi:10.1109/jiot.2020.2986110

Cited by 24 publications

(9 citation statements)

References 23 publications

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“…The average input SNR ρ is fixed at 10 dB and a bandwidth of 2 MHz is assumed. The WiFi standard IEEE 802.11ah [27] and Bluetooth 5.0 [20] are well-known examples of IoT systems operating at a 2 MHz bandwidth. The main observation from Figures 4, 5, and 6 is that for the considered target outage probability levels, the maximum EE does not occur at high ADC resolution (≥8 bits).…”

Section: Energy Efficiency and Numerical Resultsmentioning

confidence: 99%

Receiver Energy Efficiency and Transmission Latency Analysis of Outage-Constrained Differential PSK With a Finite Resolution ADC

Helwa

Al-Dhahir

2021

IEEE Access

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We consider a power constrained downlink communication scenario where energy efficiency, reliability, and latency take precedence over rate, as in some Internet of Things (IoT) applications. To reduce its receiver power consumption and complexity, we assume that the IoT device has a single RF chain and investigate the finite-resolution analog-to-digital converter (ADC) operation with differential Phase Shift Keying (PSK) modulation. A lower ADC resolution leads to an exponential decrease in power consumption, while adopting differential PSK enables the use of a low-cost detector with no channel state information (CSI) or carrier phase recovery circuitry. Our main goal in this article is to compare, both analytically and numerically using representative IoT system design parameters, the receiver energy efficiency of the proposed differential PSK system with a coherent PSK system that uses estimated CSI under reliability and latency constraints in Rayleigh slow-fading and ADC quantization distortion conditions. To mitigate the ADC finite-resolution effects without requiring CSI at the receiver or transmitter, we propose and analyze a PSK differentially-modulated Alamouti space-time block transmission scheme with only two RF chains at the transmitter while still restricting the IoT device to have a single RF chain. Our results demonstrate that in the considered low-rate, and outage and latency-constrained scenario with stringent power consumption requirements, differentially-modulated Alamouti transmissions to a single RF-chain IoT device with a lowresolution ADC is an attractive choice in terms of receiver energy efficiency, reliability, and transmission latency.

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Section: Energy Efficiency and Numerical Resultsmentioning

confidence: 99%

Receiver Energy Efficiency and Transmission Latency Analysis of Outage-Constrained Differential PSK With a Finite Resolution ADC

Helwa

Al-Dhahir

2021

IEEE Access

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“…In the formula, 1 represents the probability of belonging to the class in the original ancestor Q, and Entropy (Q) is the classification information entropy of the original ancestor Q [15]. If the ancestor Q is divided according to a certain attribute, then the sample can be partitioned according to the m different values of the sample, then the entropy required for this classification is calculated as:…”

Section: Iot Network Communication Codingmentioning

confidence: 99%

The Construction of College English Teaching Model from the Perspective of Internet-of-Things Wireless Communication

Wang

Zheng

2022

Mobile Information Systems

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The college English teaching model from the perspective of the Internet of Things is to introduce technology into the teaching process of college English. There are mainly students, teachers, and knowledge classrooms. The relationship between these roles in college English teaching is analyzed and researched. Then observing the wireless communication of the Internet of Things to manage the complex teaching management model in a hierarchical and modular form. A college English teaching model that is, constructs a student-centered, hierarchical classroom teaching model. Strengthen the cultivation of students’ language application ability through the perception of English language and comprehensive language communication. And through the analysis of the understanding of the Internet of Things and the modules of college English teaching, the students, teachers, and knowledge in the classroom are organized in the classroom as a whole. The experimental results in this paper show that through the application of Internet of Things technology in college English teaching, students’ English learning ability improves by 15–18%.

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“…For example, Microsoft Azure IoT, Amazon web service In smart cities, the WSN-IoT networks contain the connectivity technologies/protocols as shown in Table 2. Table 2 shows IoT communication technologies such as Bluetooth [10], based on IEEE 802.15.1 standards [11], RFID [12], IEEE 802.16 [13], ZigBee [14] based on IEEE 802.15.4 [15], Wi-Fi [16], based on IEEE 802.11 [17], LoRa-WAN [18] based on IEEE 802.11 series [19], 4G/5G cellular networks [20], based on WiMAX standard IEEE 802.16e [21] and 5G based on IEEE 1941 [22,23], respectively.…”

Section: Wireless Sensor Network Based Internet Of Things (Wsn-iot)mentioning

confidence: 99%

Machine Learning in Wireless Sensor Networks for Smart Cities: A Survey

Sharma¹,

2021

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Artificial intelligence (AI) and machine learning (ML) techniques have huge potential to efficiently manage the automated operation of the internet of things (IoT) nodes deployed in smart cities. In smart cities, the major IoT applications are smart traffic monitoring, smart waste management, smart buildings and patient healthcare monitoring. The small size IoT nodes based on low power Bluetooth (IEEE 802.15.1) standard and wireless sensor networks (WSN) (IEEE 802.15.4) standard are generally used for transmission of data to a remote location using gateways. The WSN based IoT (WSN-IoT) design problems include network coverage and connectivity issues, energy consumption, bandwidth requirement, network lifetime maximization, communication protocols and state of the art infrastructure. In this paper, the authors propose machine learning methods as an optimization tool for regular WSN-IoT nodes deployed in smart city applications. As per the author’s knowledge, this is the first in-depth literature survey of all ML techniques in the field of low power consumption WSN-IoT for smart cities. The results of this unique survey article show that the supervised learning algorithms have been most widely used (61%) as compared to reinforcement learning (27%) and unsupervised learning (12%) for smart city applications.

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Coexistence of Wi-Fi and IoT Communications in WLANs

Cited by 24 publications

References 23 publications

Receiver Energy Efficiency and Transmission Latency Analysis of Outage-Constrained Differential PSK With a Finite Resolution ADC

Receiver Energy Efficiency and Transmission Latency Analysis of Outage-Constrained Differential PSK With a Finite Resolution ADC

The Construction of College English Teaching Model from the Perspective of Internet-of-Things Wireless Communication

Machine Learning in Wireless Sensor Networks for Smart Cities: A Survey

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