2,544 research outputs found

    Evaluation, Modeling and Optimization of Coverage Enhancement Methods of NB-IoT

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    Narrowband Internet of Things (NB-IoT) is a new Low Power Wide Area Network (LPWAN) technology released by 3GPP. The primary goals of NB-IoT are improved coverage, massive capacity, low cost, and long battery life. In order to improve coverage, NB-IoT has promising solutions, such as increasing transmission repetitions, decreasing bandwidth, and adapting the Modulation and Coding Scheme (MCS). In this paper, we present an implementation of coverage enhancement features of NB-IoT in NS-3, an end-to-end network simulator. The resource allocation and link adaptation in NS-3 are modified to comply with the new features of NB-IoT. Using the developed simulation framework, the influence of the new features on network reliability and latency is evaluated. Furthermore, an optimal hybrid link adaptation strategy based on all three features is proposed. To achieve this, we formulate an optimization problem that has an objective function based on latency, and constraint based on the Signal to Noise Ratio (SNR). Then, we propose several algorithms to minimize latency and compare them with respect to accuracy and speed. The best hybrid solution is chosen and implemented in the NS-3 simulator by which the latency formulation is verified. The numerical results show that the proposed optimization algorithm for hybrid link adaptation is eight times faster than the exhaustive search approach and yields similar latency

    Understanding the limits of LoRaWAN

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    The quick proliferation of LPWAN networks, being LoRaWAN one of the most adopted, raised the interest of the industry, network operators and facilitated the development of novel services based on large scale and simple network structures. LoRaWAN brings the desired ubiquitous connectivity to enable most of the outdoor IoT applications and its growth and quick adoption are real proofs of that. Yet the technology has some limitations that need to be understood in order to avoid over-use of the technology. In this article we aim to provide an impartial overview of what are the limitations of such technology, and in a comprehensive manner bring use case examples to show where the limits are

    Internet of robotic things : converging sensing/actuating, hypoconnectivity, artificial intelligence and IoT Platforms

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    The Internet of Things (IoT) concept is evolving rapidly and influencing newdevelopments in various application domains, such as the Internet of MobileThings (IoMT), Autonomous Internet of Things (A-IoT), Autonomous Systemof Things (ASoT), Internet of Autonomous Things (IoAT), Internetof Things Clouds (IoT-C) and the Internet of Robotic Things (IoRT) etc.that are progressing/advancing by using IoT technology. The IoT influencerepresents new development and deployment challenges in different areassuch as seamless platform integration, context based cognitive network integration,new mobile sensor/actuator network paradigms, things identification(addressing, naming in IoT) and dynamic things discoverability and manyothers. The IoRT represents new convergence challenges and their need to be addressed, in one side the programmability and the communication ofmultiple heterogeneous mobile/autonomous/robotic things for cooperating,their coordination, configuration, exchange of information, security, safetyand protection. Developments in IoT heterogeneous parallel processing/communication and dynamic systems based on parallelism and concurrencyrequire new ideas for integrating the intelligent “devices”, collaborativerobots (COBOTS), into IoT applications. Dynamic maintainability, selfhealing,self-repair of resources, changing resource state, (re-) configurationand context based IoT systems for service implementation and integrationwith IoT network service composition are of paramount importance whennew “cognitive devices” are becoming active participants in IoT applications.This chapter aims to be an overview of the IoRT concept, technologies,architectures and applications and to provide a comprehensive coverage offuture challenges, developments and applications

    Integration of a cellular Internet-of-Things transceiver into 6G test network and evaluation of its performance

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    Abstract. This thesis focuses on the integration and deployment of an aftermarket cellular IoT transceiver on a 6G/5G test network for the purpose of evaluating the feasibility of such device for monitoring the network performance. The cellular technology employed was NB-IoT paired with a Raspberry Pi device as the microprocessor that collects network telemetry and uses MQTT protocol to provide constant data feed. The system was first tested in a public cellular network through a local service provider and was successfully connected to the network, establishing TCP/IP connections, and allowing internet connectivity. To monitor network information and gathering basic telemetry data, a network monitoring utility was developed. It collected data such as network identifiers, module registration status, band/channel, signal strength and GPS position. This data was then published to a MQTT broker. The Adafruit IO platform served as the MQTT broker, providing an interface to visualize the collected data. Furthermore, the system was configured for and deployed on a 6G/5G test network successfully. The device functionality that was developed and tested in the public network remained intact, enabling continuous monitoring and analysis of network data. Through this study, valuable insights into the integration and deployment of cellular IoT transceivers into cellular networks that employ the latest IoT technology were gained. The findings highlight the feasibility of utilizing such a system for network monitoring and demonstrate the potential for IoT applications in cellular networks

    Internet of Things and Sensors Networks in 5G Wireless Communications

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    This book is a printed edition of the Special Issue Internet of Things and Sensors Networks in 5G Wireless Communications that was published in Sensors
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