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1
Matz, Andreas Philipp, Jose-Angel Fernandez-Prieto, Joaquin Cañada-Bago, and Ulrich Birkel. "A Systematic Analysis of Narrowband IoT Quality of Service." Sensors 20, no. 6 (March 14, 2020): 1636. http://dx.doi.org/10.3390/s20061636.
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Narrowband-IoT (NB-IoT) is part of a novel group of access technologies referred to as Low-Power Wide Area Networks (LPWANs), which provide energy-efficient and long-range network access to IoT devices. Although NB-IoT Release 13 has been deployed by Mobile Network Operators (MNO), detailed Quality of Service (QoS) evaluations in public networks are still rare. In this paper, systematic physical layer measurements are conducted, and the application layer performance is verified. Special consideration is given to the influence of the radio parameters on the application layer QoS. Additionally, NB-IoT is discussed in the context of typical smart metering use cases. The results indicate that NB-IoT meets most theoretical Third Generation Partnership Project (3GPP) design goals in a commercial deployment. NB-IoT provides a wide coverage by using signal repetitions, which improve the receiver sensitivity, but simultaneously increase the system latency. The maximum data rates are consistent over a wide range of coverage situations. Overall, NB-IoT is a reliable and flexible LPWAN technology for sensor applications even under challenging radio conditions. Four smart metering transmission categories are analyzed, and NB-IoT is verified to be appropriate for applications that are not latency sensitive.
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Ugwuanyi, Stephen, Greig Paul, and James Irvine. "Survey of IoT for Developing Countries: Performance Analysis of LoRaWAN and Cellular NB-IoT Networks." Electronics 10, no. 18 (September 10, 2021): 2224. http://dx.doi.org/10.3390/electronics10182224.
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Recently, Internet of Things (IoT) deployments have shown their potential for aiding the realisation of the Sustainable Development Goals (SDGs). Concerns regarding how the IoT can specifically drive SDGs 6, 11 and 9 in developing countries have been raised with respect to the challenges of deploying licensed and unlicensed low-power wide area network (LPWAN) IoT technologies and their opportunities for IoT consumers and service providers. With IoT infrastructure and protocols being ubiquitous and each being proposed for different SDGs, we review and compare the various performance characteristics of LoRaWAN and NB-IoT networks. From the performance analysis of our networks, NB-IoT, one of the standardised promising cellular IoT solutions for developing countries, is more expensive and less energy-efficient than LoRaWAN. Utilising the same user equipment (UE), NB-IoT consumed an excess of 2 mAh of power for joining the network and 1.7 mAh more for a 44-byte uplink message compared to LoRaWAN. However, NB-IoT has the advantage of reliably and securely delivering higher network connection capacity in IoT use cases, leveraging existing cellular infrastructure. With a maximum throughput of 264 bps at 837 ms measured latency, NB-IoT outperformed LoRaWAN and proved robust for machine-type communications. These findings will help IoT consumers and service providers understand the performance differences and deployment challenges of NB-IoT and LoRaWAN and establish new research directions to tackle IoT issues in developing countries. With Nigeria as a case study, for consumers and organisations at a crossroads in their long-term deployment decisions, the proposed LPWAN integrated architecture is an example of the deployment opportunities for consumer and industrial IoT applications in developing countries.
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Zhong, Han, Ruize Sun, Fengcheng Mei, Yong Chen, Fan Jin, and Lei Ning. "Deep Grid Scheduler for 5G NB-IoT Uplink Transmission." Security and Communication Networks 2021 (August 13, 2021): 1–10. http://dx.doi.org/10.1155/2021/5263726.
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Since the birth of narrowband Internet of Things (NB-IoT), the Internet of Things (IoT) industry has made a considerable progress in the application for smart cities, smart manufacturing, and healthcare. Therefore, the number of UEs is increasing exponentially, which brings considerable pressure to the efficient resource allocation for the bandwidth and power constrained NB-IoT networks. In view of the conventional algorithms that cannot dynamically adjust resource allocation, resulting in a low resource utilization and prone to resource fragmentation, this paper proposes a double deep Q-network (DDQN)-based NB-IoT dynamic resource allocation algorithm. It first builds an NB-IoT environment model based on the real environment. Then, the DDQN algorithm interacts with the NB-IoT environment model to learn and optimize resource allocation strategies until it converges to the optimum. Finally, the simulation results show that the DDQN-based NB-IoT dynamic resource allocation algorithm is better than the traditional algorithm in the resource utilization, average transmission rate, and UE average queuing time.
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Peruzzi, Giacomo, and Alessandro Pozzebon. "Combining LoRaWAN and NB-IoT for Edge-to-Cloud Low Power Connectivity Leveraging on Fog Computing." Applied Sciences 12, no. 3 (January 30, 2022): 1497. http://dx.doi.org/10.3390/app12031497.
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Low Power Wide Area Networks (LPWANs) play crucial roles in the implementation of low-power and low-cost wide area distributed systems. Currently, two enabling technologies are the main competitors within the connectivity field for the Internet of Things (IoT), primarily because of their scalability, wide range and low power features: Long Range Wide Area Network (LoRaWAN) and Narrowband IoT (NB-IoT). In this paper, a brand new network architecture is presented, which combines both aforementioned technologies. Such a network accounts for sensor nodes, multi-protocol gateways, an a cloud infrastructure. Sensor nodes may be alternatively provided with LoRaWAN or NB-IoT. Multi-protocol gateways can receive and demodulate LoRaWAN packets and upload them to the cloud via the Message Queue Telemetry Transport (MQTT) protocol over NB-IoT. The cloud is transparent with respect to the transmission technology, meaning that data are acquired and stored regardless of the exploited technique (i.e., LoRaWAN or NB-IoT). Indeed, sensor nodes using NB-IoT can send data to the cloud and can directly communicate with other NB-IoT nodes setting up a fog computing paradigm on peer-to-peer subnetworks. This approach may be crucial for the development of complex IoT infrastructures while providing high flexibility.
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Dangana, Muhammad, Shuja Ansari, Qammer H. Abbasi, Sajjad Hussain, and Muhammad Ali Imran. "Suitability of NB-IoT for Indoor Industrial Environment: A Survey and Insights." Sensors 21, no. 16 (August 5, 2021): 5284. http://dx.doi.org/10.3390/s21165284.
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The Internet of Things (IoT) and its applications in industrial settings are set to bring in the fourth industrial revolution. The industrial environment consisting of high profile manufacturing plants and a variety of equipment is inherently characterized by high reflectiveness, causing significant multi-path components that affect the propagation of wireless communications—a challenge among others that needs to be resolved. This paper provides a detailed insight into Narrow-Band IoT (NB-IoT), Industrial IoT (IIoT), and Wireless Sensor Networks (WSN) within the context of indoor industrial environments. It presents the applications of NB-IoT for industrial settings, such as the challenges associated with these applications. Furthermore, future research directions were put forth in the areas of NB-IoT network management using self-organizing network (SON) technology, edge computing for scalability enhancement, security in NB-IoT generated data, and proposing a suitable propagation model for reliable wireless communications.
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Khan, Sikandar Zulqarnain, Yannick Le Moullec, and Muhammad Mahtab Alam. "An NB-IoT-Based Edge-of-Things Framework for Energy-Efficient Image Transfer." Sensors 21, no. 17 (September 3, 2021): 5929. http://dx.doi.org/10.3390/s21175929.
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Machine Learning (ML) techniques can play a pivotal role in energy efficient IoT networks by reducing the unnecessary data from transmission. With such an aim, this work combines a low-power, yet computationally capable processing unit, with an NB-IoT radio into a smart gateway that can run ML algorithms to smart transmit visual data over the NB-IoT network. The proposed smart gateway utilizes supervised and unsupervised ML algorithms to optimize the visual data in terms of their size and quality before being transmitted over the air. This relaxes the channel occupancy from an individual NB-IoT radio, reduces its energy consumption and also minimizes the transmission time of data. Our on-field results indicate up to 93% reductions in the number of NB-IoT radio transmissions, up to 90.5% reductions in the NB-IoT radio energy consumption and up to 90% reductions in the data transmission time.
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Salva-Garcia, Pablo, Jose M. Alcaraz-Calero, Qi Wang, Jorge Bernal Bernabe, and Antonio Skarmeta. "5G NB-IoT: Efficient Network Traffic Filtering for Multitenant IoT Cellular Networks." Security and Communication Networks 2018 (December 10, 2018): 1–21. http://dx.doi.org/10.1155/2018/9291506.
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Internet of Things (IoT) is a key business driver for the upcoming fifth-generation (5G) mobile networks, which in turn will enable numerous innovative IoT applications such as smart city, mobile health, and other massive IoT use cases being defined in 5G standards. To truly unlock the hidden value of such mission-critical IoT applications in a large scale in the 5G era, advanced self-protection capabilities are entailed in 5G-based Narrowband IoT (NB-IoT) networks to efficiently fight off cyber-attacks such as widespread Distributed Denial of Service (DDoS) attacks. However, insufficient research has been conducted in this crucial area, in particular, few if any solutions are capable of dealing with the multiple encapsulated 5G traffic for IoT security management. This paper proposes and prototypes a new security framework to achieve the highly desirable self-organizing networking capabilities to secure virtualized, multitenant 5G-based IoT traffic through an autonomic control loop featured with efficient 5G-aware traffic filtering. Empirical results have validated the design and implementation and demonstrated the efficiency of the proposed system, which is capable of processing thousands of 5G-aware traffic filtering rules and thus enables timely protection against large-scale attacks.
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De Nardis, Luca, Giuseppe Caso, Özgü Alay, Marco Neri, Anna Brunstrom, and Maria-Gabriella Di Benedetto. "Positioning by Multicell Fingerprinting in Urban NB-IoT Networks." Sensors 23, no. 9 (April 25, 2023): 4266. http://dx.doi.org/10.3390/s23094266.
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Narrowband Internet of Things (NB-IoT) has quickly become a leading technology in the deployment of IoT systems and services, owing to its appealing features in terms of coverage and energy efficiency, as well as compatibility with existing mobile networks. Increasingly, IoT services and applications require location information to be paired with data collected by devices; NB-IoT still lacks, however, reliable positioning methods. Time-based techniques inherited from long-term evolution (LTE) are not yet widely available in existing networks and are expected to perform poorly on NB-IoT signals due to their narrow bandwidth. This investigation proposes a set of strategies for NB-IoT positioning based on fingerprinting that use coverage and radio information from multiple cells. The proposed strategies were evaluated on two large-scale datasets made available under an open-source license that include experimental data from multiple NB-IoT operators in two large cities: Oslo, Norway, and Rome, Italy. Results showed that the proposed strategies, using a combination of coverage and radio information from multiple cells, outperform current state-of-the-art approaches based on single cell fingerprinting, with a minimum average positioning error of about 20 m when using data for a single operator that was consistent across the two datasets vs. about 70 m for the current state-of-the-art approaches. The combination of data from multiple operators and data smoothing further improved positioning accuracy, leading to a minimum average positioning error below 15 m in both urban environments.
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Qiu, Wenying, Sijia He, and Weixi Gu. "Research on the Integration of Wireless Sensor Networks Based on IoT Technology." Journal of Physics: Conference Series 2477, no. 1 (April 1, 2023): 012075. http://dx.doi.org/10.1088/1742-6596/2477/1/012075.
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Abstract Wireless Sensor Network (WSN) is a wireless network formed by a group of sensors with wireless transceiver capabilities, connected in a multi-hop autonomous manner. It has several advantages: low traffic, greater stability, longer wireless communication, and higher coverage areas at a lower cost. The incorporation of new NB-IoT technologies in wireless sensor networks, combining the advantages of both and the establishment of NB-IoT-based wireless sensor networks, has a very promising application in defense and military, medical, intelligent transportation, and commercial applications. This study first investigates both WSN and NB-IoT technologies separately and then combines them to investigate the networking structure of NB-IoT and WSN as well as the related technologies based on the fusion. Then the coverage method of the traditional network node redeployment of wireless sensors is described, and many problems such as poor node connectivity and low coverage are caused by the traditional method due to the lack of local search of subgroup nodes. The initialization of the nodes is carried out. The global information exchange is combined with the subgroup to determine the detectable area of the wireless sensor, and the calculus method is used for the irregular area to obtain the optimal network node so that the nodes of the wireless sensor network can be redeployed.
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Althobaiti, Ohood Saud, and Mischa Dohler. "Narrowband-Internet of Things Device-to-Device Simulation: An Open-Sourced Framework." Sensors 21, no. 5 (March 5, 2021): 1824. http://dx.doi.org/10.3390/s21051824.
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Narrowband-Internet of Things (NB-IoT) displays high-quality connectivity underpinned by fifth-generation (5G) networks to cover a wide array of IoT applications. The devices’ development and integration into different smart systems require permanent control, supervision, and the study of power consumption models to determine the performance of the network topology and allow for the measurement of the efficiency of the network topology’s application. This paper reports on an architecture and open-sourced simulation that was developed to study NB-IoT in Device-to-Device (D2D) mode, which includes the Physical (PHY), network, and application layers, as well as a queuing model, the model for uplink and downlink delays, the throughput, the overall NB-IoT D2D network performance, and the energy consumption based on the Low Energy Adaptive Clustering Hierarchy (LEACH) protocol. Our results prove that the suggested framework contributes to a reduction in power consumption, a minimization of queuing delays, a decrease in communication cost, a reduction in inter-cluster collisions, and the prevention of attacks from malicious nodes. Consequently, the framework manages the battery’s State of Charge (SOC), improves the battery’s State of Health (SOH), and maximizes the whole network lifetime. The proposed framework, the code of which has been open-sourced, can be effectively used for scientific research and development purposes to evaluate different parameters and improve the planning of NB-IoT networks.
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Bani-Yaseen, Tahani, Ashraf Tahat, Kira Kastell, and Talal A. Edwan. "Denial-of-Sleep Attack Detection in NB-IoT Using Deep Learning." Journal of Telecommunications and the Digital Economy 10, no. 3 (September 21, 2022): 14–38. http://dx.doi.org/10.18080/jtde.v10n3.532.
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With increasing Internet-of-Things (IoT) protocols and connectivity, a growing number of attacks are emerging in the associated networks. This work presents approaches using deep learning (DL) to detect attacks in an IoT environment, particularly in narrowband Internet-of-Things (NB-IoT). By virtue of its low cost, low complexity and limited energy, an NB-IoT device will not likely permit cutting-edge security mechanisms, leaving it vulnerable to, for example, denial-of-sleep (DoSl) attacks. For performance analysis, a NB-IoT network was simulated, using ns-3, to generate a novel dataset to represent an implementation of DoSl attacks. After preprocessing, the dataset was presented to a collection of machine learning (ML) models to evaluate their performance. The considered DL recurrent neural network (RNN) models have proven capable of reliably classifying traffic, with very high accuracy, into either a DoSl attack or a normal record. The performance of a long short-term memory (LSTM) classifier has provided accuracies up to 98.99%, with a detection time of 2.54 x 10-5 second/record, surpassing performance of a gated recurrent unit (GRU). RNN DL models have superior performance in terms of accuracy of detecting DoSl attacks in NB-IoT networks, when compared with other ML algorithms, including support vector machine, Gaussian naïve-Bayes, and logistic regression.
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Kadusic, Esad, Natasa Zivic, Christoph Ruland, and Narcisa Hadzajlic. "A Smart Parking Solution by Integrating NB-IoT Radio Communication Technology into the Core IoT Platform." Future Internet 14, no. 8 (July 25, 2022): 219. http://dx.doi.org/10.3390/fi14080219.
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With the emerging Internet of Things (IoT) technologies, the smart city paradigm has become a reality. Wireless low-power communication technologies (LPWAN) are widely used for device connection in smart homes, smart lighting, mitering, and so on. This work suggests a new approach to a smart parking solution using the benefits of narrowband Internet of Things (NB-IoT) technology. NB-IoT is an LPWAN technology dedicated to sensor communication within 5G mobile networks. This paper proposes the integration of NB-IoT into the core IoT platform, enabling direct sensor data navigation to the IoT radio stations for processing, after which they are forwarded to the user application programming interface (API). Showcasing the results of our research and experiments, this work suggests the ability of NB-IoT technology to support geolocation and navigation services, as well as payment and reservation services for vehicle parking to make the smart parking solutions smarter.
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Andrabi, Umer Mukhtar, Sergey N. Stepanov, Juvent Ndayikunda, and Margarita G. Kanishcheva. "CELLULAR NETWORK RESOURCE DISTRIBUTION METHODS FOR THE JOINT SERVICING OF REAL-TIME MULTISERVICE TRAFFIC AND GROUPED IOT TRAFFIC." T-Comm 14, no. 10 (2020): 61–69. http://dx.doi.org/10.36724/2072-8735-2020-14-10-61-69.
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Immense growth in the volumes and multiplicity of data to be collected in future Internet of Things (IoT) applications is one of the crucial challenges for the networking organizations as they develop from 4G+ to true 5G systems. Particularly bulk of this traffic includes complex, unstructured and varied data (Big Data) evolve from smart networking ecosystems (LTE-devices, NB-IoT devices). Although 5G offers many low power wide area technologies (Lora WAN, GSM and NB-IoT etc.), principally NB-IoT seems very promising addressing the problem because of its certain characteristics like high fault tolerance, delay tolerance, higher coverage area etc. However, due to the limited bandwidth (180 kHz) availability one of the challenges is how to efficiently use these resources to support and handle massive number of growing IoT devices, also resource management and allocation methodology between LTE and NB-IoT traffic flows. In this context, several key issues for IoT communications in 5G networks should be addressed to satisfy quality of service (QoS) provisioning. In this paper, we proposed a mathematical model for Operator Surveillance systems for sharing radio resources between LTE and NB-IoT. The model utilizes the technique of network slicing for resource management. The proposed techniques provide scenarios that aims to offer a trade-off between the two types of traffics by guaranteeing the network performance and avoiding unproductive utilization of available resources.
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Lin, Jun, Zhiqi Shen, Chunyan Miao, and Siyuan Liu. "Using blockchain to build trusted LoRaWAN sharing server." International Journal of Crowd Science 1, no. 3 (September 4, 2017): 270–80. http://dx.doi.org/10.1108/ijcs-08-2017-0010.
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Purpose With the rapid growth of the Internet of Things (IoT) market and requirement, low power wide area (LPWA) technologies have become popular. In various LPWA technologies, Narrow Band IoT (NB-IoT) and long range (LoRa) are two main leading competitive technologies. Compared with NB-IoT networks, which are mainly built and managed by mobile network operators, LoRa wide area networks (LoRaWAN) are mainly operated by private companies or organizations, which suggests two issues: trust of the private network operators and lack of network coverage. This study aims to propose a conceptual architecture design of a blockchain built-in solution for LoRaWAN network servers to solve these two issues for LoRaWAN IoT solution. Design/methodology/approach The study proposed modeling, model analysis and architecture design. Findings The proposed solution uses the blockchain technology to build an open, trusted, decentralized and tamper-proof system, which provides the indisputable mechanism to verify that the data of a transaction has existed at a specific time in the network. Originality/value To the best of our knowledge, this is the first work that integrates blockchain technology and LoRaWAN IoT technology.
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Hu, Zhenxian, Guangtao Xue, Yichao Chen, Minglu Li, Ming Wang, and Feng Lv. "City-Wide NB-IoT Network Monitoring and Diagnosing." Wireless Communications and Mobile Computing 2022 (April 11, 2022): 1–14. http://dx.doi.org/10.1155/2022/3153274.
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NarrowBand-IoT (NB-IoT) is a radio-access technology standardized by 3GPP to support a large set of use cases associated with the rapid deployment of massive machine-type communications. NB-IoT facilitates the connection of devices in inaccessible areas, extends battery life, and reduces device complexity. Unfortunately, the opacity of the underlying schema (i.e., the way that these benefits are achieved) makes it very difficult for most users and developers to manage deployment scenarios. In this study, we built an embedded system comprising a Raspberry Pi with an NB module, referred to as NBPilot, which interacts with NB networks to identify essential signaling messages transmitted by a Qualcomm NB modem. This system gives researchers and developers an unprecedented understanding of network behavior as well as the ability to adjust them to their particular requirements. We employed the-state-of-the-art machine learning techniques for modeling and the analysis of NB performance. The efficacy of the proposed NBPilot system was established by applying it to a metropolitan NB-IoT network with over 2,000 NB sites for the collection and testing of data trace as well as the validation of a cellular station prior to going online. The developed machine learning techniques predict the actual performance (rate, delay, and power consumption) of the user equipment’s connection against the QoS advertised by the operator and pinpoint the affecting factors.
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Chen, Yating, Lingyun Lu, Xiaohan Yu, and Xiang Li. "Adaptive Method for Packet Loss Types in IoT: An Naive Bayes Distinguisher." Electronics 8, no. 2 (January 28, 2019): 134. http://dx.doi.org/10.3390/electronics8020134.
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With the rapid development of IoT (Internet of Things), massive data is delivered through trillions of interconnected smart devices. The heterogeneous networks trigger frequently the congestion and influence indirectly the application of IoT. The traditional TCP will highly possible to be reformed supporting the IoT. In this paper, we find the different characteristics of packet loss in hybrid wireless and wired channels, and develop a novel congestion control called NB-TCP (Naive Bayesian) in IoT. NB-TCP constructs a Naive Bayesian distinguisher model, which can capture the packet loss state and effectively classify the packet loss types from the wireless or the wired. More importantly, it cannot cause too much load on the network, but has fast classification speed, high accuracy and stability. Simulation results using NS2 show that NB-TCP achieves up to 0.95 classification accuracy and achieves good throughput, fairness and friendliness in the hybrid network.
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Metwaly, Samar Shaker, Ahmed M. Abd El-Haleem, and Osama El-Ghandour. "No-Regret Matching Game Algorithm for NOMA Based UAV-Assisted NB-IoT Systems." Ingénierie des systèmes d information 26, no. 1 (February 28, 2021): 79–85. http://dx.doi.org/10.18280/isi.260108.
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NB-IoT is the standardized technology for machine type communication (MTC) in Long Term Evolution (LTE). NB-IoT can achieve IoT requirements nevertheless, it suffers a low rate and capacity. On the other hand, Unmanned aerial vehicles (UAV) and Non-Orthogonal Multiple Access (NOMA) are promising technology used to enhance the throughput, capacity, and coverage of wireless communication networks. In this paper, we propose a heterogeneous network scenario where a UAV small Base Station (UBS) is used to assist the LTE Macro Base Station (MBS) with the help of the Non-Orthogonal Multiple Access technique to solve the NB-IoT throughput and capacity issues. Matching game based no-regret learning algorithm is proposed to optimize the NB-IoT device association and using NOMA pairing at each base station to provide the maximum system total rate and capacity. Simulation results show that our proposed scheme increases the total rate of the system by 60% and the system capacity by at least 80%, compared to NOMA without UAV and the total rate and capacity of the system by 200% and 85% respectively, with OMA scheme.
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Mignardi, Silvia, Riccardo Marini, Roberto Verdone, and Chiara Buratti. "On the Performance of a UAV-Aided Wireless Network Based on NB-IoT." Drones 5, no. 3 (September 9, 2021): 94. http://dx.doi.org/10.3390/drones5030094.
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In recent years, interest in Unmanned Aerial Vehicles (UAVs) as a means to provide wireless connectivity has substantially increased thanks to their easy, fast and flexible deployment. Among the several possible applications of UAV networks explored by the current literature, they can be efficiently employed to collect Internet-of-Things (IoT) data because the non-stringent latency and small-size traffic type is particularly suited for UAVs’ inherent characteristics. However, the implications coming from the implementation of existing technology in such kinds of nodes are not straightforward. In this article, we consider a Narrow Band IoT (NB-IoT) network served by a UAV base station. Because of the many configurations possible within the NB-IoT standard, such as the access structure and numerology, we thoroughly review the technical aspects that have to be implemented and may be affected by the proposed UAV-aided IoT network. For proper remarks, we investigate the network performance jointly in terms of the number of successful transmissions, access rate, latency, throughput and energy consumption. Then, we compare the obtained results on different and known trajectories in the research community and study the impact of varying UAV parameters such as speed and height. Moreover, the numerical assessment allows us to extend the discussion to the potential implications of this model in different scenarios. Thus, this article summarizes all the main aspects that must be considered in planning NB-IoT networks with UAVs.
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Brinkley, Alex. "Rival Networks Emerge to Capitalise on 5G." New Electronics 51, no. 18 (October 8, 2019): 34–35. http://dx.doi.org/10.12968/s0047-9624(22)61440-8.
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Rival networks emerge to capitalise on 5G The advent of 5G sees two network standards emerge to exploit the connectivity that it offers. Alex Brinkley considers the performance and merits of NB-IoT and LoRaWAN
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García-Martín, Juan Pablo, and Antonio Torralba. "Model of a Device-Level Combined Wireless Network Based on NB-IoT and IEEE 802.15.4 Standards for Low-Power Applications in a Diverse IoT Framework." Sensors 21, no. 11 (May 26, 2021): 3718. http://dx.doi.org/10.3390/s21113718.
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With the development of the Internet of Things (IoT), Low Data Rate-Personal Area Networks (LR-WPAN) have been deployed for different applications. Now comes the need to integrate these networks in search of greater connectivity, performances, and geographic coverage. This integration is facilitated by the recent deployment of low power wide area networks (LPWAN) in the licensed bands, especially narrowband IoT (NB-IoT) and long-term evolution for machine-type communications (LTE-M), which are standardized technologies that will continue evolving as part of the fifth generation (5G) specifications. This paper proposes a design methodology for combined networks using LR-WPAN and LPWAN technologies. These networks are combined at the device level using a cluster-tree topology. An example is shown here, where an existing IEEE 802.15.4 network is combined with NB-IoT. To this end, new dual nodes are incorporated, acting as cluster heads. The paper discusses the different aspects of formation and operation of the combined network. A dynamic link selection (DLS) algorithm is also proposed, based on which cluster headers dynamically determine the preferred link, depending on link quality and type of traffic. Extensive simulations show that the DLS algorithm significantly increases battery life on dual nodes, which are the nodes with the highest power demands.
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Beshley, Mykola, Natalia Kryvinska, Marian Seliuchenko, Halyna Beshley, Elhadi M. Shakshuki, and Ansar-Ul-Haque Yasar. "End-to-End QoS “Smart Queue” Management Algorithms and Traffic Prioritization Mechanisms for Narrow-Band Internet of Things Services in 4G/5G Networks." Sensors 20, no. 8 (April 19, 2020): 2324. http://dx.doi.org/10.3390/s20082324.
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This paper proposes a modified architecture of the Long-Term Evolution (LTE) mobile network to provide services for the Internet of Things (IoT). This is achieved by allocating a narrow bandwidth and transferring the scheduling functions from the eNodeB base station to an NB-IoT controller. A method for allocating uplink and downlink resources of the LTE/NB-IoT hybrid technology is applied to ensure the Quality of Service (QoS) from end-to-end. This method considers scheduling traffic/resources on the NB-IoT controller, which allows eNodeB planning to remain unchanged. This paper also proposes a prioritization approach within the IoT traffic to provide End-to-End (E2E) QoS in the integrated LTE/NB-IoT network. Further, we develop “smart queue” management algorithms for the IoT traffic prioritization. To demonstrate the feasibility of our approach, we performed a number of experiments using simulations. We concluded that our proposed approach ensures high end-to-end QoS of the real-time traffic by reducing the average end-to-end transmission delay.
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Ndayikunda, Juven. "QUALITY OF SERVICE ASSESSMENT IN LTE NETWORKS WITH A LIMITED NUMBER OF USERS." SYNCHROINFO JOURNAL 6, no. 3 (2020): 14–19. http://dx.doi.org/10.36724/2664-066x-2020-6-2-14-19.
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Narrow Band Internet of Things (NB-IoT) is the latest cellular radio access technology that was based on LTE technology and implemented as part of the 3GPP 3GPP 3GPP for Low-power Wide-area Network (LPWAN). The paper considers the features of NB-IoT standards based on the characteristics of the physical and channel layers of NB-IoT technology based on release 14-15 of the 3GPP group. The aim of this work is also to build and study a model for serving heterogeneous traffic in an isolated cell of the LTE standard, which supports the functionality of the Internet of Things IoT (Internet of Things), in particular eMTC (enhanced Machine Type Communication). The constructed mathematical model takes into account the heterogeneity of the arrival of requests and their dependence on the number of users of cellular services. Depending on the number of sources, incoming requests are described by Poisson or Engset models. The studied model makes it possible to dynamically allocate resources that have LTE.
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Mwakwata, Collins Burton, Hassan Malik, Muhammad Mahtab Alam, Yannick Le Moullec, Sven Parand, and Shahid Mumtaz. "Narrowband Internet of Things (NB-IoT): From Physical (PHY) and Media Access Control (MAC) Layers Perspectives." Sensors 19, no. 11 (June 8, 2019): 2613. http://dx.doi.org/10.3390/s19112613.
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Narrowband internet of things (NB-IoT) is a recent cellular radio access technology based on Long-Term Evolution (LTE) introduced by Third-Generation Partnership Project (3GPP) for Low-Power Wide-Area Networks (LPWAN). The main aim of NB-IoT is to support massive machine-type communication (mMTC) and enable low-power, low-cost, and low-data-rate communication. NB-IoT is based on LTE design with some changes to meet the mMTC requirements. For example, in the physical (PHY) layer only single-antenna and low-order modulations are supported, and in the Medium Access Control (MAC) layers only one physical resource block is allocated for resource scheduling. The aim of this survey is to provide a comprehensive overview of the design changes brought in the NB-IoT standardization along with the detailed research developments from the perspectives of Physical and MAC layers. The survey also includes an overview of Evolved Packet Core (EPC) changes to support the Service Capability Exposure Function (SCEF) to manage both IP and non-IP data packets through Control Plane (CP) and User Plane (UP), the possible deployment scenarios of NB-IoT in future Heterogeneous Wireless Networks (HetNet). Finally, existing and emerging research challenges in this direction are presented to motivate future research activities.
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Miao, Yiming, Yuanwen Tian, Jingjing Cheng, M. Shamim Hossain, and Ahmed Ghoneim. "RADB: Random Access with Differentiated Barring for Latency-Constrained Applications in NB-IoT Network." Wireless Communications and Mobile Computing 2018 (2018): 1–9. http://dx.doi.org/10.1155/2018/6210408.
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With the development of LPWA (Low Power Wide Area) technology, the emerging NB-IoT (Narrowband Internet of Things) technology is becoming popular with wide area and low-data-rate services. In order to achieve objectives such as huge amount of connection and wide area coverage within NB-IoT, the problem of network congestion generated by random access of numerous devices should be solved. In this paper, we first introduce the background of NB-IoT and investigate the research on random access optimization algorithm. Then we summarize relevant features of NB-IoT uplink and narrowband physical random access channel and design random access with differentiated barring (RADB), which can improve the insufficiency of traditional dynamic access class barring method. At last, the algorithms proposed in this paper are realized with established NB-IoT model using OPNET Modeler platform, and simulations are conducted. The simulation results show that RADB is able to effectively solve preamble request conflict generated by random access of numerous devices and preferentially provide efficient and reliable random access for latency-sensitive devices.
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Abostait, Abdallah, Rania M. Tawfik, M. Saeed Darweesh, and Hassan Mostafa. "Design and FPGA-Based Hardware Implementation of NB-IoT Physical Uplink Shared Channel Transmitter and Physical Downlink Shared Channel Receiver." Electronics 12, no. 9 (April 24, 2023): 1966. http://dx.doi.org/10.3390/electronics12091966.
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With the anticipated growth of the internet of things (IoT) market, many low-power wide-area (LPWA) technologies have been introduced to connect a wide range of IoT devices with varying performance requirements. The narrowband internet of things (NB-IoT) is a 3rd generation partnership project (3GPP) standardized LPWA technology that meets most IoT service requirements. In this paper, the design and implementation of the physical uplink transmitting chain as well as the physical downlink receiving chain of the NB-IoT user equipment (UE) are presented. Both chains’ main blocks are designed to follow the 3GPP NB-IoT LTE standard Release 14 (Rel-14). The whole design is experimentally implemented on the Virtex 7 (VC 709) Connectivity kit, and all performance metrics are reported. Moreover, an NB-IoT base station is implemented and integrated with the two prototyped UEs to set-up an NB-IoT system, which is employed to send data from one UE to another UE through the NB-IoT base station using two FPGAs (one to implement the sending UE and the other one to implement the receiving UE) and three universal software radio peripherals (USRPs) B200 (one to implement the RF front-end of the transmitting UE FPGA, one to implement the base station RF front-end, and one to implement the RF front-end of the receiving UE FPGA). Experimental results show that the implemented NB-IoT system is working successfully, as the two NB-IoT UEs communicate together successfully through the NB-IoT base station and exchange the data properly.
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Wu, Xiaojun, Qiying Cao, Juan Jin, Yuanjie Li, and Hong Zhang. "Nodes Availability Analysis of NB-IoT Based Heterogeneous Wireless Sensor Networks under Malware Infection." Wireless Communications and Mobile Computing 2019 (January 3, 2019): 1–9. http://dx.doi.org/10.1155/2019/4392839.
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The Narrowband Internet of Things (NB-IoT) is a main stream technology based on mobile communication system. The combination of NB-IoT and WSNs can active the application of WSNs. In order to evaluate the influence of node heterogeneity on malware propagation in NB-IoT based Heterogeneous Wireless Sensor Networks, we propose a node heterogeneity model based on node distribution and vulnerability differences, which can be used to analyze the availability of nodes. We then establish the node state transition model by epidemic theory and Markov chain. Further, we obtain the dynamic equations of the transition between nodes and the calculation formula of node availability. The simulation result is that when the degree of node is small and the node vulnerability function is a power function, the node availability is the highest; when the degree of node is large and the node vulnerability function satisfies the exponential function and the power function, the node availability is high. Therefore, when constructing a NBIOT-HWSNs network, node protection is implemented according to the degree of node, so that when the node vulnerability function satisfies the power function, all nodes can maintain high availability, thus making the entire network more stable.
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Janssen, Thomas, Rafael Berkvens, and Maarten Weyn. "RSS-Based Localization and Mobility Evaluation Using a Single NB-IoT Cell." Sensors 20, no. 21 (October 29, 2020): 6172. http://dx.doi.org/10.3390/s20216172.
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Low Power Wide Area Networks (LPWAN) have the ability to localize a mobile transmitter using signals of opportunity, as a low power and low cost alternative to satellite-based solutions. In this paper, we evaluate the accuracy of three localization approaches based on the Received Signal Strength (RSS). More specifically, the performance of a proximity, range-based and optimized fingerprint-based algorithm is evaluated in a large-scale urban environment using a public Narrowband Internet of Things (NB-IoT) network. The results show a mean location estimation error of 340, 320 and 204 m, respectively. During the measurement campaign, we discovered a mobility issue in NB-IoT. In contrast to other LPWAN and cellular technologies which use multiple gateways or cells to locate a device, only a single cell antenna can be used for RSS-based localization in NB-IoT. Therefore, we address this limitation in the current NB-IoT hardware and software by studying the mobility of the cellular-based 3GPP standard in a localization context. Experimental results show that the lack of handover support leads to increased cell reselection time and poor cell sector reliability, which in turn results in reduced localization performance.
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Xu, Jie. "Big NB-IoT Data: Enhancing Portability of Handheld Narrow-Band Internet of Things Performance on Big Data Technology." Mobile Information Systems 2021 (July 12, 2021): 1–6. http://dx.doi.org/10.1155/2021/1872140.
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The Narrow Band-Internet of Things (NB-IoT) is a wideband radio technology developed for the Internet of Things that enables smoother- and farther-reaching connectivity between IoT devices. In addition to traditional network optimization devices, Bluetooth and Wi-Fi, its virtue is low cost, and it consumes less energy and has high coverage and extended battery life. In order to secure the balance of task execution latency across NB-IoT devices, in this research work, we design a handheld NB-IoT wireless communication device. Furthermore, we provide realistic resource-sharing methods between multimedia and sensor data in NB-IoT wireless deployment by our accurate analytical methodology. In addition, we have considerably enhanced technology for gathering Big Data from several scattered sources, in combination with advancements in big data processing methodologies. The proposed handheld terminal has a wide variety of commercial applications in intelligent manufacturing and smart parking. Simulation outcomes illustrate the benefits of our handheld terminal, which provides practical solutions for network optimization, improving market share and penetration rate.
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Yang, Siming, Zheng Shan, Jiang Cao, Yuan Gao, Yang Guo, Ping Wang, Jing Wang, and Xiaonan Wang. "A Novel Path Planning and Node Selection Method Using Reinforcement Learning in NTN IoT Networks." Wireless Communications and Mobile Computing 2022 (September 16, 2022): 1–14. http://dx.doi.org/10.1155/2022/5265038.
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With the rapid deployment of 5G networks in recent years, the characteristics of high bandwidth, low latency, and low energy consumption of 5G networks have enabled the rapid development of IoT (Internet of things) technology. However, 5G networks cannot provide high-quality wireless coverage for many IoT devices in border areas and hotspots with a high signal density that lack fixed infrastructure. Therefore, this paper uses the UAV (unmanned aerial vehicle) to carry the communication platform to build the NTN (nonterrestrial network) to provide wireless coverage for terrestrial fixed and mobile IoT devices. Meanwhile, since the NTN needs to provide wireless coverage for many IoT devices, we use deep reinforcement learning to provide path planning for the UAV communication platform to improve the efficiency of wireless coverage. We build a simulation environment to evaluate the performance of the NTN network for wireless coverage of IoT devices in urban hotspot areas. Experimental results show that the method proposed in this paper can provide higher downlink rates for more IoT devices than NB-IoT (narrowband Internet of things).
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Sanchez-Gomez, Jesus, Dan Garcia-Carrillo, Rafael Marin-Perez, and Antonio Skarmeta. "Secure Authentication and Credential Establishment in Narrowband IoT and 5G." Sensors 20, no. 3 (February 7, 2020): 882. http://dx.doi.org/10.3390/s20030882.
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Security is critical in the deployment and maintenance of novel IoT and 5G networks. The process of bootstrapping is required to establish a secure data exchange between IoT devices and data-driven platforms. It entails, among other steps, authentication, authorization, and credential management. Nevertheless, there are few efforts dedicated to providing service access authentication in the area of constrained IoT devices connected to recent wireless networks such as narrowband IoT (NB-IoT) and 5G. Therefore, this paper presents the adaptation of bootstrapping protocols to be compliant with the 3GPP specifications in order to enable the 5G feature of secondary authentication for constrained IoT devices. To allow the secondary authentication and key establishment in NB-IoT and 4G/5G environments, we have adapted two Extensible Authentication Protocol (EAP) lower layers, i.e., PANATIKI and LO-CoAP-EAP. In fact, this approach presents the evaluation of both aforementioned EAP lower layers, showing the contrast between a current EAP lower layer standard, i.e., PANA, and one specifically designed with the constraints of IoT, thus providing high flexibility and scalability in the bootstrapping process in 5G networks. The proposed solution is evaluated to prove its efficiency and feasibility, being one of the first efforts to support secure service authentication and key establishment for constrained IoT devices in 5G environments.
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Turzhanova, Karina, Sergey Konshin, Valery Tikhvinskiy, and Alexandr Solochshenko. "Performance evaluation of NB-IoT in-band deployment mode in suburban area." Indonesian Journal of Electrical Engineering and Computer Science 23, no. 2 (August 1, 2021): 855. http://dx.doi.org/10.11591/ijeecs.v23.i2.pp855-862.
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There given to discuss the study results about one of three deployment scenarios performance (in-band deployment mode) of the narrow-band internet of things (NB-IoT) technology. The study is carrying out with help of simulation modeling and experimental testing of the main network parameters, namely: radio coverage, network capacity, user experience, and their dependencies on each other. Comparison of the results of a physical experiment and simulation modeling shows their high convergence and confirms the adequacy of the applied testing methodology. As a case scenario provided an example of NB-IoT implementation on a 4G mobile network in the 800 MHz band, in a suburban area for remote metering applications. The article presents the applying testing methodology of NB-IoT that adapted to the local conditions of radio network planning. Based on the obtained data, adducing the main conclusions about the feasibility of using an in-band scenario for deploying NB-IoT on a 4G network in a suburban environment.
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Martinez Alonso, Rodney, David Plets, Ernesto Fontes Pupo, Margot Deruyck, Luc Martens, Glauco Guillen Nieto, and Wout Joseph. "IoT-Based Management Platform for Real-Time Spectrum and Energy Optimization of Broadcasting Networks." Wireless Communications and Mobile Computing 2018 (July 11, 2018): 1–14. http://dx.doi.org/10.1155/2018/7287641.
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We investigate the feasibility of Internet of Things (IoT) technology to monitor and improve the energy efficiency and spectrum usage efficiency of broadcasting networks in the Ultra-High Frequency (UHF) band. Traditional broadcasting networks are designed with a fixed radiated power to guarantee a certain service availability. However, excessive fading margins often lead to inefficient spectrum usage, higher interference, and power consumption. We present an IoT-based management platform capable of dynamically adjusting the broadcasting network radiated power according to the current propagation conditions. We assess the performance and benchmark two IoT solutions (i.e., LoRa and NB-IoT). By means of the IoT management platform the broadcasting network with adaptive radiated power reduces the power consumption by 15% to 16.3% and increases the spectrum usage efficiency by 32% to 35% (depending on the IoT platform). The IoT feedback loop power consumption represents less than 2% of the system power consumption. In addition, white space spectrum availability for secondary wireless telecommunications services is increased by 34% during 90% of the time.
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Liang, Jia-Ming, Kun-Ru Wu, Jen-Jee Chen, Pei-Yi Liu, and Yu-Chee Tseng. "Energy-Efficient Uplink Resource Units Scheduling for Ultra-Reliable Communications in NB-IoT Networks." Wireless Communications and Mobile Computing 2018 (July 2, 2018): 1–17. http://dx.doi.org/10.1155/2018/4079017.
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For 5G wireless communications, the 3GPP Narrowband Internet of Things (NB-IoT) is one of the most promising technologies, which provides multiple types of resource unit (RU) with a special repetition mechanism to improve the scheduling flexibility and enhance the coverage and transmission reliability. Besides, NB-IoT supports different operation modes to reuse the spectrum of LTE and GSM, which can make use of bandwidth more efficiently. The IoT application grows rapidly; however, those massive IoT devices need to operate for a very long time. Thus, the energy consumption becomes a critical issue. Therefore, NB-IoT provides discontinuous reception operation to save devices’ energy. But, how to further reduce the transmission energy while ensuring the required ultra-reliability is still an open issue. In this paper, we study how to guarantee the reliable communication and satisfy the quality of service (QoS) while minimizing the energy consumption for IoT devices. We first model the problem as an optimization problem and prove it to be NP-complete. Then, we propose an energy-efficient, ultra-reliable, and low-complexity scheme, which consists of two phases. The first phase tries to optimize the default transmit configurations of devices which incur the lowest energy consumption and satisfy the QoS requirement. The second phase leverages a weighting strategy to balance the emergency and inflexibility for determining the scheduling order to ensure the delay constraint while maintaining energy efficiency. Extensive simulation results show that our scheme can serve more devices with guaranteed QoS while saving their energy effectively.
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Ali, Md Sadek, Yu Li, Md Khalid Hossain Jewel, Oluwole John Famoriji, and Fujiang Lin. "Channel Estimation and Peak-to-Average Power Ratio Analysis of Narrowband Internet of Things Uplink Systems." Wireless Communications and Mobile Computing 2018 (July 5, 2018): 1–15. http://dx.doi.org/10.1155/2018/2570165.
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Narrowband Internet of Things (NB-IoT) is a cellular based promising low-power wide-area network (LPWN) technology standardized by the 3rd Generation Partnership Project (3GPP) in release-13 as a part of the future 5th Generation (5G) wireless communication systems. The main design target of NB-IoT was to enhance radio coverage by repeating signal over an additional period of time for the ultralow-end IoT devices that would be operated in extreme coverage environments. But the power efficiency of the low-cost NB-IoT user equipment (NB-IoT UE) in the uplink is the major concern. Coverage improvement from signal repetitions depends on the channel estimation quality at extremely bad radio conditions. The typical operating signal-to-noise ratio (SNR) for NB-IoT is expected to be much lower than the zero. In this paper, we have proposed two efficient narrowband demodulation reference signal (NDMRS)-assisted channel estimation algorithms based on the conventional least squares (LS) and minimum mean square error (MMSE) estimation methods. The theoretical analysis and the link-level performance of our proposed estimation methods are presented. Simulation results exhibit that the proposed methods provide better estimation precision compared to the traditional LS and MMSE methods at the low SNR situations. Furthermore, we have analyzed the raised-cosine (RC) and square-root-raised cosine (RRC) pulse shaping to reduce peak-to-average power ratio (PAPR) as an uplink transmit filter. The PAPR values are evaluated through extensive computer simulations for both single-tone and multi-tone transmissions. Our evaluation results vindicate that the RRC pulse shaping with lower PAPR values is feasible to design of practical NB-IoT uplink transmitter and increases power efficiency.
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El Mahjoubi, Ahmed, Tomader Mazri, and Nabil Hmina. "NB-IoT and eMTC: Engineering results towards 5G/IoT Mobile Technologies." International Journal of Interactive Mobile Technologies (iJIM) 13, no. 01 (January 29, 2019): 115. http://dx.doi.org/10.3991/ijim.v13i01.9728.
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5G RF technology is an essential part of the wireless mobile technology. Technically, 5G is predicted to empower people-thing and thing-thing interconnections by combining wireless technologies and networks. Our university has been actively support research on 4G/5G/IoT, in which the NB-IoT, eMTC and Massive Carrier Aggregation new features challenge are of big interest. New 5G trials put forward a lot of prerequisites for new RF interface in terms of radio bandwidth, power issues, as well as the huge number of connections for IoT capacity management and optimization. Based on Morocco’s current situation, this paper first discusses the 5G technologies; In addition, we will discuss IoT SoftRadio application support, and NB-IoT master plan recap. At last, based on the current plan of 5G RF KPIs management according to first Morocco 5G trail Results and Deployment plans.
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Gbadamosi, Safiu Abiodun, Gerhard P. Hancke, and Adnan M. Abu-Mahfouz. "Building Upon NB-IoT Networks: A Roadmap Towards 5G New Radio Networks." IEEE Access 8 (2020): 188641–72. http://dx.doi.org/10.1109/access.2020.3030653.
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Nashiruddin, Muhammad Imam, Maruli Tua Baja Sihotang, and Muhammad Ary Murti. "Comparative study of low power wide area network based on internet of things for smart city deployment in Bandung city." Indonesian Journal of Electrical Engineering and Computer Science 25, no. 1 (January 1, 2022): 425. http://dx.doi.org/10.11591/ijeecs.v25.i1.pp425-439.
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Smart city implementation, such as smart energy and utilities, smart mobility & transportation, smart environment, and smart living in urban areas is expanding rapidly worldwide. However, one of the biggest challenges that need to be solved is the selection of the appropriate internet of things (IoT) connectivity technologies. This research will seek for the best candidate low power wide area network (LPWAN) technologies such as long-range wide area network (LoRaWAN), narrow-band internet of things (NB-IoT), and random phase multiple access (RPMA) for IoT smart city deployment in Bandung city is based on IoT network connectivity between with six technical evaluation criteria: gateway requirements, traffic/data projection, the best signal level area distribution, and overlapping zones. Bass model is carried out to determine the capacity forecast. While in coverage prediction, LoRaWAN and NB-IoT use the Okumura-Hata propagation, and Erceg-Greenstein (SUI) model is used for RPMA. Based on the simulation and performance evaluation results, RPMA outperforms LoRaWAN and NB-IoT. It required the least gateway number to cover Bandung city with the best signal levels and overlapping zones.
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Istiana, Tri, R. Yudha Mardyansyah, and G. S. Budhi Dharmawan. "Kajian Pemanfaatan IoT Berbasis LPWAN Untuk Jaringan Akuisisi Data ARG." Elektron : Jurnal Ilmiah 12, no. 1 (May 4, 2020): 1–6. http://dx.doi.org/10.30630/eji.12.1.155.
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One of parameters for observing weather elements is the amount of rainfall. The rainfall observation system is using ARG. The existing condition uses cellular network-based IoT. In this study, researchers tried to provide an alternative communication system for ARG data acquisition networks using LPWAN-based IoT technology. Comparison of three LPWAN IoT technologies that can be applied to ARG communication systems, namely NB-IoT, Sigfox, and LoRaWAN. The three LPWAN technologies have followed the Republic of Indonesia Minister of Communication and Information Regulation No. 1 of 2019. These three technologies can be used for ARG data acquisition networks. LoRaWAN technology in rural areas reaches 20 km. LoRaWAN devices that meet frequency requirements have been sold freely on the internet with the 920 MHz frequency band. Of these three technologies, only LoRaWAN can be used to build private or internal communication networks. This is an added value for BMKG to build district or provincial scale LPWA WAN networks in regions that are constrained by the transmission of ARG data through cellular networks.
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Lee, Jinseong, and Jaiyong Lee. "Prediction-Based Energy Saving Mechanism in 3GPP NB-IoT Networks." Sensors 17, no. 9 (September 1, 2017): 2008. http://dx.doi.org/10.3390/s17092008.
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Yu, Ya-Ju. "NPDCCH Period Adaptation and Downlink Scheduling for NB-IoT Networks." IEEE Internet of Things Journal 8, no. 2 (January 15, 2021): 962–75. http://dx.doi.org/10.1109/jiot.2020.3010532.
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Jiang, Nan, Yansha Deng, Arumugam Nallanathan, and Jonathon A. Chambers. "Reinforcement Learning for Real-Time Optimization in NB-IoT Networks." IEEE Journal on Selected Areas in Communications 37, no. 6 (June 2019): 1424–40. http://dx.doi.org/10.1109/jsac.2019.2904366.
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Singh, Ritesh Kumar, Priyesh Pappinisseri Puluckul, Rafael Berkvens, and Maarten Weyn. "Energy Consumption Analysis of LPWAN Technologies and Lifetime Estimation for IoT Application." Sensors 20, no. 17 (August 25, 2020): 4794. http://dx.doi.org/10.3390/s20174794.
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The spectrum of Internet of Things (IoT) applications is exponentially growing, driving the demand for better energy performance metrics. In conjunction, Low Power Wide Area Networks (LPWAN) have evolved as long-range connectivity enabler with low management cost. The integration of LPWAN communication assists in reliable IoT operation with extended lifetime. Notable LPWAN technologies that contend for many of the IoT applications are LoRaWAN, DASH7, Sigfox, and NB-IoT. Most of the end-devices such as sensors and actuators are battery powered, therefore investigating energy consumption becomes crucial. To estimate the consumed power, it is important to analyze the energy consumption in wireless communication. This paper describes an empirical evaluation of energy consumption for LPWAN wireless technologies. We measure the current consumption of LoRaWAN, DASH7, Sigfox, and NB-IoT and derive the respective battery lifetime. These measurements help to quantify the energy performance of different protocols. We observe that LoRaWAN and DASH7 are more energy efficient when compared to Sigfox and NB-IoT. Finally, a case study on energy consumption is done on precision agriculture in the greenhouse, showing that battery lifetime in real applications can drop significantly from the ideal case. These results can be used for increasing the effectiveness of the IoT application by selecting the right technology and battery capacity.
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Hadjadj-Aoul, Yassine, and Soraya Ait-Chellouche. "Access Control in NB-IoT Networks: A Deep Reinforcement Learning Strategy." Information 11, no. 11 (November 23, 2020): 541. http://dx.doi.org/10.3390/info11110541.
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The Internet of Things (IoT) is a key enabler of the digital mutation of our society. Driven by various services and applications, Machine Type Communications (MTC) will become an integral part of our daily life, over the next few years. Meeting the ITU-T requirements, in terms of density, battery longevity, coverage, price, and supported mechanisms and functionalities, Cellular IoT, and particularly Narrowband-IoT (NB-IoT), is identified as a promising candidate to handle massive MTC accesses. However, this massive connectivity would pose a huge challenge for network operators in terms of scalability. Indeed, the connection to the network in cellular IoT passes through a random access procedure and a high concentration of IoT devices would, very quickly, lead to a bottleneck. The latter procedure needs, then, to be enhanced as the connectivity would be considerable. With this in mind, we propose, in this paper, to apply the access class barring (ACB) mechanism to regulate the number of devices competing for the access. In order to derive the blocking factor, we formulated the access problem as a Markov decision process that we were able to solve using one of the most advanced deep reinforcement learning techniques. The evaluation of the proposed access control, through simulations, shows the effectiveness of our approach compared to existing approaches such as the adaptive one and the Proportional Integral Derivative (PID) controller. Indeed, it manages to keep the proportion of access attempts close to the optimum, despite the lack of accurate information on the number of access attempts.
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Yassine, Farah, Melhem El Helou, Samer Lahoud, and Oussama Bazzi. "Energy-Efficient Uplink Scheduling in Narrowband IoT." Sensors 22, no. 20 (October 12, 2022): 7744. http://dx.doi.org/10.3390/s22207744.
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This paper presents a detailed study of uplink scheduling in narrowband internet of things (NB-IoT) networks. As NB-IoT devices need a long battery lifetime, we aim to maximize energy efficiency while satisfying the main requirements for NB-IoT devices. Also, as the NB-IoT scheduling problem is divided into link adaptation problem and resource allocation problem, this paper investigates the correlation between these two problems. Accordingly, we propose two scheduling schemes: the joint scheduling scheme, where the two problems are combined as one optimization problem, and the successive scheduling scheme that manages each problem separately but successively. Each scheme aims to maximize energy efficiency while achieving reliable transmission, satisfying delay requirements, and guaranteeing resource allocation specifications. Also, we investigate the impact of the selected devices to be served on the total energy efficiency. Accordingly, we propose two device selection techniques to maximize the total energy efficiency. The first technique exhaustively searches for the optimal devices, while the second sorts the devices based on a proposed priority score. The simulation results compare the successive and the joint scheduling schemes. The results show that the joint scheme outperforms the successive scheme in terms of energy efficiency and the number of served devices but with higher complexity. Also, the results highlight the impact of each proposed selection technique on the scheduling schemes’ performance.
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Aldabbagh, Ghadah, Nikos Dimitriou, Samar Alkhuraiji, and Omaimah Bamasag. "Radio Coverage and Device Capacity Dimensioning Methodologies for IoT LoRaWAN and NB-IoT Deployments in Urban Environments." Future Internet 13, no. 6 (May 30, 2021): 144. http://dx.doi.org/10.3390/fi13060144.
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This paper focuses on the study of IoT network deployments, in both unlicensed and licensed bands, considering LoRaWAN and NB-IoT standards, respectively. The objective is to develop a comprehensive and detailed network planning and coverage dimensioning methodology for assessing key metrics related to the achieved throughput and capacity for specific requirements in order to identify tradeoffs and key issues that are related to the applicability of IoT access technologies for representative use case types. This paper will provide a concise overview of key characteristics of IoT representative IoT access network standards that are considered for being deployed in unlicensed and licensed bands and will present a methodology for modeling the characteristics of both access network technologies in order to assess their coverage and capacity considering different parameters.
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Wang, Lijun, Chengguang Wang, Xu Lu, Dongzhi Ping, Shitong Jiang, Xinxin Wang, and Jianyong Zhang. "A Design for a Lithium-Ion Battery Pack Monitoring System Based on NB-IoT-ZigBee." Electronics 12, no. 17 (August 23, 2023): 3561. http://dx.doi.org/10.3390/electronics12173561.
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With environmental issues arising from the excessive use of fossil fuels, clean energy has gained widespread attention, particularly the application of lithium-ion batteries. Lithium-ion batteries are integrated into various industrial products, which necessitates higher safety requirements. Narrowband Internet of Things (NB-IoT) is an LPWA (Low Power Wide Area Network) technology that provides IoT devices with low-power, low-cost, long-endurance, and wide-coverage wireless connectivity. This study addresses the shortcomings of existing lithium-ion battery pack detection systems and proposes a lithium-ion battery monitoring system based on NB-IoT-ZigBee technology. The system operates in a master-slave mode, with the subordinate module collecting and fusing multi-source sensor data, while the master control module uploads the data to local monitoring centers and cloud platforms via TCP and NB-IoT. Experimental validation demonstrates that the design functions effectively, accomplishing the monitoring and protection of lithium-ion battery packs in energy storage power stations.
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Chen, Yen-Wen, and Guan-Yi Xue. "The Adaptive Random Access Carrier Allocation Scheme in NB-IoT Networks." Communications and Network 14, no. 01 (2022): 1–11. http://dx.doi.org/10.4236/cn.2022.141001.
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Deng, Xianjun, Zujun Tang, Lingzhi Yi, and Laurence T. Yang. "Healing Multimodal Confident Information Coverage Holes in NB-IoT-Enabled Networks." IEEE Internet of Things Journal 5, no. 3 (June 2018): 1463–73. http://dx.doi.org/10.1109/jiot.2017.2783258.
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Goulart, Ana, Anitha Chennamaneni, Damiano Torre, Byul Hur, and Fadhil Y. Al-Aboosi. "On Wide-Area IoT Networks, Lightweight Security and Their Applications—A Practical Review." Electronics 11, no. 11 (June 2, 2022): 1762. http://dx.doi.org/10.3390/electronics11111762.
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The Internet of Things (IoT) allows users to collect sensor data, control devices, and analyze collected data over the Internet. IoT devices are located in diverse environments and support many applications. To protect IoT systems from cyber threats, Confidentiality, Integrity, and Authentication—the CIA triad—must be supported. However, IoT devices have limited energy and computational resources. Lightweight encryption algorithms have been proposed for IoT, and have been reviewed by previous studies. Some cover communication protocols, while others cover lightweight security or review the challenges in implementing a secure IoT system. The aim of this literature review is to combine the first two topics: communication protocols and lightweight security. They will be approached from a practitioner’s standpoint. Several applications are provided that help readers with a minor background in security to understand these technologies and which elements of the CIA triad have more priority. This paper describes wide-area IoT networks, such as LoRAWAN, Sigfox, and NB-IoT, and their security. It also describes applications throughout the world, and how to enhance their security by implementing emerging lightweight security—specifically, approaches to make well-known ciphers such as Advanced Encryption Standard (AES) and Elliptic Curve Cryptography (ECC) more lightweight.
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Leenders, Guus, Gilles Callebaut, Geoffrey Ottoy, Liesbet Van der Perre, and Lieven De Strycker. "Multi-RAT for IoT: The Potential in Combining LoRaWAN and NB-IoT." IEEE Communications Magazine 59, no. 12 (December 2021): 98–104. http://dx.doi.org/10.1109/mcom.008.2100382.
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