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Journal articles on the topic 'Low Power Wide Area'

Author: Grafiati
Published: 28 June 2021
Last updated: 13 February 2022

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1

Raza, Usman, Parag Kulkarni, and Mahesh Sooriyabandara. "Low Power Wide Area Networks: An Overview." IEEE Communications Surveys & Tutorials 19, no. 2 (2017): 855–73. http://dx.doi.org/10.1109/comst.2017.2652320.

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2

Thubert, Pascal, Alexander Pelov, and Suresh Krishnan. "Low-Power Wide-Area Networks at the IETF." IEEE Communications Standards Magazine 1, no. 1 (March 2017): 76–79. http://dx.doi.org/10.1109/mcomstd.2017.1600002st.

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3

Qin, Zhijin, Frank Y. Li, Geoffrey Ye Li, Julie A. McCann, and Qiang Ni. "Low-Power Wide-Area Networks for Sustainable IoT." IEEE Wireless Communications 26, no. 3 (June 2019): 140–45. http://dx.doi.org/10.1109/mwc.2018.1800264.

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4

Saifullah, Abusayeed, Mahbubur Rahman, Dali Ismail, Chenyang Lu, Jie Liu, and Ranveer Chandra. "Low-Power Wide-Area Network Over White Spaces." IEEE/ACM Transactions on Networking 26, no. 4 (August 2018): 1893–906. http://dx.doi.org/10.1109/tnet.2018.2856197.

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5

Gu, Fei, Jianwei Niu, Landu Jiang, Xue Liu, and Mohammed Atiquzzaman. "Survey of the low power wide area network technologies." Journal of Network and Computer Applications 149 (January 2020): 102459. http://dx.doi.org/10.1016/j.jnca.2019.102459.

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6

Georgiou, Orestis, and Usman Raza. "Low Power Wide Area Network Analysis: Can LoRa Scale?" IEEE Wireless Communications Letters 6, no. 2 (April 2017): 162–65. http://dx.doi.org/10.1109/lwc.2016.2647247.

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7

Arsalan Jawed, Syed, Waqar Ahmed Qureshi, Atia Shafique, Junaid Ali Qureshi, Abdul Hameed, and Moaaz Ahmed. "Low-power area-efficient wide-range robust CMOS temperature sensors." Microelectronics Journal 44, no. 2 (February 2013): 119–27. http://dx.doi.org/10.1016/j.mejo.2012.10.002.

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8

Moons, Bart, Abdulkadir Karaagac, Eli De Poorter, and Jeroen Hoebeke. "Efficient Vertical Handover in Heterogeneous Low-Power Wide-Area Networks." IEEE Internet of Things Journal 7, no. 3 (March 2020): 1960–73. http://dx.doi.org/10.1109/jiot.2019.2961950.

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9

Jiang, Xiaofan, Heng Zhang, Edgardo Alberto Barsallo Yi, Nithin Raghunathan, Charilaos Mousoulis, Somali Chaterji, Dimitrios Peroulis, Ali Shakouri, and Saurabh Bagchi. "Hybrid Low-Power Wide-Area Mesh Network for IoT Applications." IEEE Internet of Things Journal 8, no. 2 (January 15, 2021): 901–15. http://dx.doi.org/10.1109/jiot.2020.3009228.

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10

Kang, James, and Sasan Adibi. "Bushfire Disaster Monitoring System Using Low Power Wide Area Networks (LPWAN)." Technologies 5, no. 4 (October 8, 2017): 65. http://dx.doi.org/10.3390/technologies5040065.

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11

Kim, Byoungwook, and Kwang-il Hwang. "Cooperative Downlink Listening for Low-Power Long-Range Wide-Area Network." Sustainability 9, no. 4 (April 17, 2017): 627. http://dx.doi.org/10.3390/su9040627.

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12

Janssen, Thomas, Maarten Weyn, and Rafael Berkvens. "Localization in Low Power Wide Area Networks Using Wi-Fi Fingerprints." Applied Sciences 7, no. 9 (September 12, 2017): 936. http://dx.doi.org/10.3390/app7090936.

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13

Lieske, Hendrik, Gerd Kilian, Marco Breiling, Sebastian Rauh, Joerg Robert, and Albert Heuberger. "Decoding Performance in Low-Power Wide Area Networks With Packet Collisions." IEEE Transactions on Wireless Communications 15, no. 12 (December 2016): 8195–208. http://dx.doi.org/10.1109/twc.2016.2613079.

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14

Mahfoudi, Mohamed N., Gayatri Sivadoss, Othmane B. Korachi, Thierry Turletti, and Walid Dabbous. "Joint range extension and localization for low-power wide-area network." Internet Technology Letters 2, no. 5 (July 24, 2019): e120. http://dx.doi.org/10.1002/itl2.120.

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15

Aihara, Naoki, Koichi Adachi, Osamu Takyu, Mai Ohta, and Takeo Fujii. "Generalized Interference Detection Scheme in Heterogeneous Low Power Wide Area Networks." IEEE Sensors Letters 4, no. 6 (June 2020): 1–4. http://dx.doi.org/10.1109/lsens.2020.2992723.

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16

Bembe, Mncedisi, Adnan Abu-Mahfouz, Moshe Masonta, and Tembisa Ngqondi. "A survey on low-power wide area networks for IoT applications." Telecommunication Systems 71, no. 2 (March 26, 2019): 249–74. http://dx.doi.org/10.1007/s11235-019-00557-9.

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17

Masoudi, Meysam, Amin Azari, and Cicek Cavdar. "Low Power Wide Area IoT Networks: Reliability Analysis in Coexisting Scenarios." IEEE Wireless Communications Letters 10, no. 7 (July 2021): 1405–9. http://dx.doi.org/10.1109/lwc.2021.3068815.

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18

Yu, Zhongyang, Baoming Bai, and Min Zhu. "An Efficient Frame Optimization Scheme for Low Power Wide Area Networks." IEEE Communications Letters 25, no. 5 (May 2021): 1615–19. http://dx.doi.org/10.1109/lcomm.2021.3057168.

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19

Wang, Hao, Hong Sui, Jia Li, and Jian Yao. "Research of the application of the Low Power Wide Area Network in power grid." IOP Conference Series: Materials Science and Engineering 322 (March 2018): 072021. http://dx.doi.org/10.1088/1757-899x/322/7/072021.

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20

Kim, Yi-Kang, and Seung-Yeon Kim. "Success Probability Characterization of Long-Range in Low-Power Wide Area Networks." Sensors 20, no. 23 (November 30, 2020): 6861. http://dx.doi.org/10.3390/s20236861.

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In low-power wide area networks (LPWAN), a considerable number of end devices (EDs) communicate with the gateway in a certain area, whereas for transmitted data, a low data rate and high latency are allowed. Long-range (LoRa), as one of the LPWAN technologies, considers pure ALOHA and chirp spread spectrum (CSS) in the media access control (MAC) and physical (PHY) layers such that it can improve the energy efficiency while mitigating inter-cell interference (ICI). This paper investigates the system throughput of LoRa networks under the assumption that the interferences between EDs for exclusive regions are ignored using CSS. In order to establish an analytical model for the performance of LoRa, we introduce the pure ALOHA capture model, which is the power threshold model. For this model, we assume that the interfering power is proportional to the length of the time overlapped. In addition, we discuss LoRa gain by comparing the total throughput of LoRa with that of non-CSS.
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21

Petroni, Andrea, Francesca Cuomo, Leonisio Schepis, Mauro Biagi, Marco Listanti, and Gaetano Scarano. "Adaptive Data Synchronization Algorithm for IoT-Oriented Low-Power Wide-Area Networks." Sensors 18, no. 11 (November 20, 2018): 4053. http://dx.doi.org/10.3390/s18114053.

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The Internet of Things (IoT) is by now very close to be realized, leading the world towards a new technological era where people’s lives and habits will be definitively revolutionized. Furthermore, the incoming 5G technology promises significant enhancements concerning the Quality of Service (QoS) in mobile communications. Having billions of devices simultaneously connected has opened new challenges about network management and data exchange rules that need to be tailored to the characteristics of the considered scenario. A large part of the IoT market is pointing to Low-Power Wide-Area Networks (LPWANs) representing the infrastructure for several applications having energy saving as a mandatory goal besides other aspects of QoS. In this context, we propose a low-power IoT-oriented file synchronization protocol that, by dynamically optimizing the amount of data to be transferred, limits the device level of interaction within the network, therefore extending the battery life. This protocol can be adopted with different Layer 2 technologies and provides energy savings at the IoT device level that can be exploited by different applications.
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22

Sheshalevich, Vladislav. "LPWAN – Low-power Wide-area Network. Communication for the Internet of Things." Bezopasnost informacionnyh tehnology 2017, no. 3 (August 2017): 7–17. http://dx.doi.org/10.26583/bit.2017.3.01.

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23

Shin, Joonwoo. "Channel Adaptive Bandwidth Allocation Method for Low Power Wide Area Communication Systems." Journal of Korean Institute of Communications and Information Sciences 42, no. 10 (October 31, 2017): 1863–70. http://dx.doi.org/10.7840/kics.2017.42.10.1863.

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24

Phong Truong, Tuyen, Hai Toan Le, and Tram Thi Nguyen. "A reconfigurable hardware platform for low-power wide-area wireless sensor networks." Journal of Physics: Conference Series 1432 (January 2020): 012068. http://dx.doi.org/10.1088/1742-6596/1432/1/012068.

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25

Zhang, Xihai, Yan Zhao, Lin Zhou, Jian Zhao, Wenbin Dong, Mingming Zhang, and Xitong Lv. "Transmission Tower Tilt Monitoring System Using Low-Power Wide-Area Network Technology." IEEE Sensors Journal 21, no. 2 (January 15, 2021): 1100–1107. http://dx.doi.org/10.1109/jsen.2020.3004817.

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26

He, Zhe, You Li, Ling Pei, and Kyle O'Keefe. "Enhanced Gaussian Process-Based Localization Using a Low Power Wide Area Network." IEEE Communications Letters 23, no. 1 (January 2019): 164–67. http://dx.doi.org/10.1109/lcomm.2018.2878704.

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27

Xiong, Xiong, Kan Zheng, Rongtao Xu, Wei Xiang, and Periklis Chatzimisios. "Low power wide area machine-to-machine networks: key techniques and prototype." IEEE Communications Magazine 53, no. 9 (September 2015): 64–71. http://dx.doi.org/10.1109/mcom.2015.7263374.

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28

Rahman, Mahbubur, and Abusayeed Saifullah. "Integrating Low-Power Wide-Area Networks for Enhanced Scalability and Extended Coverage." IEEE/ACM Transactions on Networking 28, no. 1 (February 2020): 413–26. http://dx.doi.org/10.1109/tnet.2020.2963886.

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29

Kawamoto, Yuichi, Ryota Sasazawa, Bomin Mao, and Nei Kato. "Multilayer Virtual Cell-Based Resource Allocation in Low-Power Wide-Area Networks." IEEE Internet of Things Journal 6, no. 6 (December 2019): 10665–74. http://dx.doi.org/10.1109/jiot.2019.2940600.

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30

Ruotsalainen, Henri, Junqing Zhang, and Stepan Grebeniuk. "Experimental Investigation on Wireless Key Generation for Low-Power Wide-Area Networks." IEEE Internet of Things Journal 7, no. 3 (March 2020): 1745–55. http://dx.doi.org/10.1109/jiot.2019.2946919.

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31

Montejo-Sanchez, Samuel, Cesar A. Azurdia-Meza, Richard Demo Souza, Evelio Martin Garcia Fernandez, Ismael Soto, and Arliones Hoeller. "Coded Redundant Message Transmission Schemes for Low-Power Wide Area IoT Applications." IEEE Wireless Communications Letters 8, no. 2 (April 2019): 584–87. http://dx.doi.org/10.1109/lwc.2018.2880959.

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32

Ray, Papia. "Power system low frequency oscillation mode estimation using wide area measurement systems." Engineering Science and Technology, an International Journal 20, no. 2 (April 2017): 598–615. http://dx.doi.org/10.1016/j.jestch.2016.11.019.

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33

Muntoni, Giacomo, Giovanni Andrea Casula, Giorgio Montisci, Tonino Pisanu, Hendrik Rogier, and Andrea Michel. "An eighth-mode SIW antenna for Low-Power Wide-Area Network applications." Journal of Electromagnetic Waves and Applications 35, no. 13 (April 22, 2021): 1815–29. http://dx.doi.org/10.1080/09205071.2021.1918264.

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34

Jin, Jie, and LV Zhao. "Low Voltage Low Power Fully Integrated Chaos Generator." Journal of Circuits, Systems and Computers 27, no. 10 (May 24, 2018): 1850155. http://dx.doi.org/10.1142/s0218126618501554.

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A low voltage low power fully integrated chaos generator is presented in this paper. Comparing with the conventional off-the-shelf electronic components-based chaos generators, the designed circuit is fully integrated, and it achieves lower supply voltage, lower power dissipation and smaller chip area. The proposed fully integrated chaos generator is verified with GlobalFoundries 0.18[Formula: see text][Formula: see text]m CMOS 1P6M RF process using Cadence IC Design Tools. The simulation results demonstrate that the fully integrated chaos generator consumes only 17[Formula: see text]mW from [Formula: see text]2.5[Formula: see text]V supply voltage. Moreover, the chip area of the chaos generator is only 1.755[Formula: see text]mm2 including the testing pads, and it has a wide range of practical application prospects.
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35

Sheikh, Muhammad Usman, Boxuan Xie, Kalle Ruttik, Hüseyin Yiğitler, Riku Jäntti, and Jyri Hämäläinen. "Ultra-Low-Power Wide Range Backscatter Communication Using Cellular Generated Carrier." Sensors 21, no. 8 (April 10, 2021): 2663. http://dx.doi.org/10.3390/s21082663.

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With the popularization of Internet-of-things (IoT) and wireless communication systems, a diverse set of applications in smart cities are emerging to improve the city-life. These applications usually require a large coverage area and minimal operation and maintenance cost. To this end, the recently emerging backscatter communication (BC) is gaining interest in both industry and academia as a new communication paradigm that provides high energy efficient communications that may even work in a battery-less mode and, thus, it is well suited for smart city applications. However, the coverage of BC in urban area deployments is not available, and the feasibility of its utilization for smart city applications is not known. In this article, we present a comprehensive coverage study of a practical cellular carrier-based BC system for indoor and outdoor scenarios in a downtown area of a Helsinki city. In particular, we evaluate the coverage outage performance of different low-power and wide area technologies, i.e., long range (LoRa) backscatter, arrow band-Internet of Things (NB-IoT), and Bluetooth low energy (BLE) based BC at different frequencies of operation. To do so, we carry out a comprehensive campaign of simulations while using a sophisticated three-dimensional (3D) ray tracing (RT) tool, ITU outdoor model, and 3rd generation partnership project (3GPP) indoor hotspot model. This study also covers the energy harvesting aspects of backscatter device, and it highlights the importance of future backscatter devices with high energy harvesting efficiency. The simulation results and discussion provided in this article will be helpful in understanding the coverage aspects of practical backscatter communication system in a smart city environment.
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36

Peruzzi, Giacomo, and Alessandro Pozzebon. "A Review of Energy Harvesting Techniques for Low Power Wide Area Networks (LPWANs)." Energies 13, no. 13 (July 3, 2020): 3433. http://dx.doi.org/10.3390/en13133433.

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The emergence of Internet of Things (IoT) architectures and applications has been the driver for a rapid growth in wireless technologies for the Machine-to-Machine domain. In this context, a crucial role is being played by the so-called Low Power Wide Area Networks (LPWANs), a bunch of transmission technologies developed to satisfy three main system requirements: low cost, wide transmission range, and low power consumption. This last requirement is especially crucial as IoT infrastructures should operate for long periods on limited quantities of energy: to cope with this limitation, energy harvesting is being applied every day more frequently, and several different techniques are being tested for LPWAN systems. The aim of this survey paper is to provide a detailed overview of the the existing LPWAN systems relying on energy harvesting for their powering. In this context, the different LPWAN technologies and protocols will be discussed and, for each technology, the applied energy harvesting techniques will be described as well as the architecture of the power management units when present.
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37

Wang, Hao, Hong Sui, Xing Liao, and Junhao Li. "Comparative analysis of the application of different Low Power Wide Area Network technologies in power grid." IOP Conference Series: Materials Science and Engineering 322 (March 2018): 072030. http://dx.doi.org/10.1088/1757-899x/322/7/072030.

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38

CHANG, ROBERT C., LUNG-CHIH KUO, and HOU-MING CHEN. "A LOW-VOLTAGE LOW-POWER CMOS PHASE-LOCKED LOOP." Journal of Circuits, Systems and Computers 14, no. 05 (October 2005): 997–1006. http://dx.doi.org/10.1142/s0218126605002738.

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A low-voltage low-power CMOS phase-locked loop (PLL) is presented in this paper. It consists of a phase frequency detector, a charge pump, a loop filter, a voltage-control oscillator, and a frequency divider. A new phase frequency detector is proposed to reduce the dead zone and the mismatch effect of the charge pump circuit. A novel charge pump circuit with a small area and wide output range is described. The PLL circuit has been designed using the TSMC 0.35 μm 1P4M CMOS technology. The chip area is 1.08 mm × 1.01 mm. The post-layout simulation results show that the frequency of 900 MHz can be generated with a single supply voltage of 1.5 V. The power dissipation of the circuit is 9.17 mW.
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39

Fernández-Garcia, Raul, and Ignacio Gil. "An Alternative Wearable Tracking System Based on a Low-Power Wide-Area Network." Sensors 17, no. 3 (March 14, 2017): 592. http://dx.doi.org/10.3390/s17030592.

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40

Xu, Rongtao, Xiong Xiong, Kan Zheng, and Xianbin Wang. "Design and prototyping of low-power wide area networks for critical infrastructure monitoring." IET Communications 11, no. 6 (April 20, 2017): 823–30. http://dx.doi.org/10.1049/iet-com.2016.0853.

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41

Ikpehai, Augustine, Bamidele Adebisi, Khaled M. Rabie, Kelvin Anoh, Ruth E. Ande, Mohammad Hammoudeh, Haris Gacanin, and Uche M. Mbanaso. "Low-Power Wide Area Network Technologies for Internet-of-Things: A Comparative Review." IEEE Internet of Things Journal 6, no. 2 (April 2019): 2225–40. http://dx.doi.org/10.1109/jiot.2018.2883728.

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42

Chen, Min, Yiming Miao, Xin Jian, Xiaofei Wang, and Iztok Humar. "Cognitive-LPWAN: Towards Intelligent Wireless Services in Hybrid Low Power Wide Area Networks." IEEE Transactions on Green Communications and Networking 3, no. 2 (June 2019): 409–17. http://dx.doi.org/10.1109/tgcn.2018.2873783.

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43

Lin, Hai, Zhihong Chen, and Lusheng Wang. "Offloading for Edge Computing in Low Power Wide Area Networks With Energy Harvesting." IEEE Access 7 (2019): 78919–29. http://dx.doi.org/10.1109/access.2019.2922399.

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44

Cui, Shengmin, and Inwhee Joe. "Collision prediction for a low power wide area network using deep learning methods." Journal of Communications and Networks 22, no. 3 (June 2020): 205–14. http://dx.doi.org/10.1109/jcn.2020.000017.

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45

Nguyen, Tung T., Ha H. Nguyen, Robert Barton, and Patrick Grossetete. "Efficient Design of Chirp Spread Spectrum Modulation for Low-Power Wide-Area Networks." IEEE Internet of Things Journal 6, no. 6 (December 2019): 9503–15. http://dx.doi.org/10.1109/jiot.2019.2929496.

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46

Lemic, Filip, Arash Behboodi, Jeroen Famaey, and Rudolf Mathar. "Location-Based Discovery and Vertical Handover in Heterogeneous Low-Power Wide-Area Networks." IEEE Internet of Things Journal 6, no. 6 (December 2019): 10150–65. http://dx.doi.org/10.1109/jiot.2019.2935804.

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47

Zhu, Hongxu, Kim Fung Tsang, Yucheng Liu, Yang Wei, Hao Wang, Chung Kit Wu, and Wai Hin Wan. "Index of Low-Power Wide Area Networks: A Ranking Solution toward Best Practice." IEEE Communications Magazine 59, no. 4 (April 2021): 139–44. http://dx.doi.org/10.1109/mcom.001.2000873.

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48

Tran, Xuan Nam, Van-Phuc Hoang, and Ba Cao Nguyen. "Combining RF energy harvesting and cooperative communications for low-power wide-area systems." AEU - International Journal of Electronics and Communications 139 (September 2021): 153909. http://dx.doi.org/10.1016/j.aeue.2021.153909.

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49

Liu, Yang, Qian Huang, and Dong Chen. "Identification the Low-Frequency Oscillation Stakeout of Power System by Wide-Area Measurement System." Applied Mechanics and Materials 128-129 (October 2011): 594–601. http://dx.doi.org/10.4028/www.scientific.net/amm.128-129.594.

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With the rapid development of interconnected power grid, the phenomenon of power system low-frequency oscillation appears unavoidably. Then, the appearance of wide-area measurement system provided a supporting technology for better scout low-frequency oscillation system and better recognize the oscillation mode . In this paper, the existing oscillation mode identifying methods are analyzed from the viewpoint of calculation speed, criterion, calculation accuracy, etc. Mainly compared the applicability of two methods, Prony and ESPRIT . Based on the above research, a new idea of monitoring power system low frequency oscillation based on WAMS is put forward in this paper.
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50

Zanaj, Eljona, Giuseppe Caso, Luca De Nardis, Alireza Mohammadpour, Özgü Alay, and Maria-Gabriella Di Benedetto. "Energy Efficiency in Short and Wide-Area IoT Technologies—A Survey." Technologies 9, no. 1 (March 19, 2021): 22. http://dx.doi.org/10.3390/technologies9010022.

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In the last years, the Internet of Things (IoT) has emerged as a key application context in the design and evolution of technologies in the transition toward a 5G ecosystem. More and more IoT technologies have entered the market and represent important enablers in the deployment of networks of interconnected devices. As network and spatial device densities grow, energy efficiency and consumption are becoming an important aspect in analyzing the performance and suitability of different technologies. In this framework, this survey presents an extensive review of IoT technologies, including both Low-Power Short-Area Networks (LPSANs) and Low-Power Wide-Area Networks (LPWANs), from the perspective of energy efficiency and power consumption. Existing consumption models and energy efficiency mechanisms are categorized, analyzed and discussed, in order to highlight the main trends proposed in literature and standards toward achieving energy-efficient IoT networks. Current limitations and open challenges are also discussed, aiming at highlighting new possible research directions.
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