6,999 research outputs found

    Wireless powered D2D communications underlying cellular networks: design and performance of the extended coverage

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    Because of the short battery life of user equipments (UEs), and the requirements for better quality of service have been more demanding, energy efficiency (EE) has emerged to be important in device-to-device (D2D) communications. In this paper, we consider a scenario, in which D2D UEs in a half-duplex decode-and-forward cognitive D2D communication underlying a traditional cellular network harvest energy and communicate with each other by using the spectrum allocated by the base station (BS). In order to develop a practical design, we achieve the optimal time switching (TS) ratio for energy harvesting. Besides that, we derive closed-form expressions for outage probability, sum-bit error rate, average EE and instantaneous rate by considering the scenario when installing the BS near UEs or far from the UEs. Two communication types are enabled by TS-based protocol. Our numerical and simulation results prove that the data rate of the D2D communication can be significantly enhanced.Web of Science58439939

    Sustainable Radio Frequency Wireless Energy Transfer for Massive Internet of Things

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    Reliable energy supply remains a crucial challenge in the Internet of Things (IoT). Although relying on batteries is cost-effective for a few devices, it is neither a scalable nor a sustainable charging solution as the network grows massive. Besides, current energy-saving technologies alone cannot cope, for instance, with the vision of zero-energy devices and the deploy-and-forget paradigm which can unlock a myriad of new use cases. In this context, sustainable radio frequency wireless energy transfer emerges as an attractive solution for efficiently charging the next generation of ultra low power IoT devices. Herein, we highlight that sustainable charging is broader than conventional green charging, as it focuses on balancing economy prosperity and social equity in addition to environmental health. Moreover, we overview the key enablers for realizing this vision and associated challenges. We discuss the economic implications of powering energy transmitters with ambient energy sources, and reveal insights on their optimal deployment. We highlight relevant research challenges and candidate solutions.Comment: 12 pages, 6 figures, 2 tables, submitted to IEEE Internet of Things Journa

    An Integrated environment for data acquisition with dynamic changes in wireless sensor networks

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    The wireless sensor network (WSN) is an important technology with a wide variety of diverse applications in such domains as healthcare, military forces and environmental monitoring. Our research aims at developing methods and tools capable of addressing WSN problems such as energy constraint, low memory, and computation capability of a sensor node by implementing a new WSN design concept, improving existing and developing new protocols. Our research goal is to develop novel generic methodologies supporting a higher level of design flexibility and possible architectural optimization against multiple criteria such as the quality of data (QoD), quality of service (QoS), and lifetime extension. Application requirements may vary in terms of abovementioned parameters and consequently there is no single platform that can be applied to all domains. Moreover, current methods do not provide opportunities for dynamic changes of either protocols or their parameters, which might improve WSN agility and survivability in a harsh environment. This problem can be solved by integrating various protocols at different layers within a single framework and supporting their dynamic selection in order to adapt the network to varying application requirements. This thesis develops a mechanism which facilitates structural design and implementation of an Integrated Environment for Data Acquisition with Dynamic Changes (IEDADC). It features adaptation and integration of protocols, protocol switching and automatic or manual selection as well as the implementation of quality assurance and localization techniques. The design methodology is tested by implementing a SN prototype consisting of a base station and sensor nodes. Sun Small Programmable Object Technology is used as a hardware basis for this work. The software has been developed in Java programming language including the host and sensor nodes\u27 applications. The conducted experiments have confirmed the higher level of design flexibility and optimization of the following criteria: energy consumption, QoD and QoS

    Resource Allocation in Wireless Networks with RF Energy Harvesting and Transfer

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    Radio frequency (RF) energy harvesting and transfer techniques have recently become alternative methods to power the next generation of wireless networks. As this emerging technology enables proactive replenishment of wireless devices, it is advantageous in supporting applications with quality-of-service (QoS) requirement. This article focuses on the resource allocation issues in wireless networks with RF energy harvesting capability, referred to as RF energy harvesting networks (RF-EHNs). First, we present an overview of the RF-EHNs, followed by a review of a variety of issues regarding resource allocation. Then, we present a case study of designing in the receiver operation policy, which is of paramount importance in the RF-EHNs. We focus on QoS support and service differentiation, which have not been addressed by previous literatures. Furthermore, we outline some open research directions.Comment: To appear in IEEE Networ

    Study on Different Topology Manipulation Algorithms in Wireless Sensor Network

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    Wireless sensor network (WSN) comprises of spatially distributed autonomous sensors to screen physical or environmental conditions and to agreeably go their information through the network to a principle area. One of the critical necessities of a WSN is the efficiency of vitality, which expands the life time of the network. At the same time there are some different variables like Load Balancing, congestion control, coverage, Energy Efficiency, mobility and so on. A few methods have been proposed via scientists to accomplish these objectives that can help in giving a decent topology control. In the piece, a few systems which are accessible by utilizing improvement and transformative strategies that give a multi target arrangement are examined. In this paper, we compare different algorithms' execution in view of a few parameters intended for every target and the outcomes are analyzed. DOI: 10.17762/ijritcc2321-8169.15029

    Survey on wireless technology trade-offs for the industrial internet of things

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    Aside from vast deployment cost reduction, Industrial Wireless Sensor and Actuator Networks (IWSAN) introduce a new level of industrial connectivity. Wireless connection of sensors and actuators in industrial environments not only enables wireless monitoring and actuation, it also enables coordination of production stages, connecting mobile robots and autonomous transport vehicles, as well as localization and tracking of assets. All these opportunities already inspired the development of many wireless technologies in an effort to fully enable Industry 4.0. However, different technologies significantly differ in performance and capabilities, none being capable of supporting all industrial use cases. When designing a network solution, one must be aware of the capabilities and the trade-offs that prospective technologies have. This paper evaluates the technologies potentially suitable for IWSAN solutions covering an entire industrial site with limited infrastructure cost and discusses their trade-offs in an effort to provide information for choosing the most suitable technology for the use case of interest. The comparative discussion presented in this paper aims to enable engineers to choose the most suitable wireless technology for their specific IWSAN deployment

    Energy-Sustainable IoT Connectivity: Vision, Technological Enablers, Challenges, and Future Directions

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    Technology solutions must effectively balance economic growth, social equity, and environmental integrity to achieve a sustainable society. Notably, although the Internet of Things (IoT) paradigm constitutes a key sustainability enabler, critical issues such as the increasing maintenance operations, energy consumption, and manufacturing/disposal of IoT devices have long-term negative economic, societal, and environmental impacts and must be efficiently addressed. This calls for self-sustainable IoT ecosystems requiring minimal external resources and intervention, effectively utilizing renewable energy sources, and recycling materials whenever possible, thus encompassing energy sustainability. In this work, we focus on energy-sustainable IoT during the operation phase, although our discussions sometimes extend to other sustainability aspects and IoT lifecycle phases. Specifically, we provide a fresh look at energy-sustainable IoT and identify energy provision, transfer, and energy efficiency as the three main energy-related processes whose harmonious coexistence pushes toward realizing self-sustainable IoT systems. Their main related technologies, recent advances, challenges, and research directions are also discussed. Moreover, we overview relevant performance metrics to assess the energy-sustainability potential of a certain technique, technology, device, or network and list some target values for the next generation of wireless systems. Overall, this paper offers insights that are valuable for advancing sustainability goals for present and future generations.Comment: 25 figures, 12 tables, submitted to IEEE Open Journal of the Communications Societ

    NOMA based resource allocation and mobility enhancement framework for IoT in next generation cellular networks

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    With the unprecedented technological advances witnessed in the last two decades, more devices are connected to the internet, forming what is called internet of things (IoT). IoT devices with heterogeneous characteristics and quality of experience (QoE) requirements may engage in dynamic spectrum market due to scarcity of radio resources. We propose a framework to efficiently quantify and supply radio resources to the IoT devices by developing intelligent systems. The primary goal of the paper is to study the characteristics of the next generation of cellular networks with non-orthogonal multiple access (NOMA) to enable connectivity to clustered IoT devices. First, we demonstrate how the distribution and QoE requirements of IoT devices impact the required number of radio resources in real time. Second, we prove that using an extended auction algorithm by implementing a series of complementary functions, enhance the radio resource utilization efficiency. The results show substantial reduction in the number of sub-carriers required when compared to conventional orthogonal multiple access (OMA) and the intelligent clustering is scalable and adaptable to the cellular environment. Ability to move spectrum usages from one cluster to other clusters after borrowing when a cluster has less user or move out of the boundary is another soft feature that contributes to the reported radio resource utilization efficiency. Moreover, the proposed framework provides IoT service providers cost estimation to control their spectrum acquisition to achieve required quality of service (QoS) with guaranteed bit rate (GBR) and non-guaranteed bit rate (Non-GBR)

    Optimizing communication and computation for multi-UAV information gathering applications

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    Typical mobile agent networks, such as multi-UAV systems, are constrained by limited resources: energy, computing power, memory and communication bandwidth. In particular, limited energy affects system performance directly, such as system lifetime. Moreover, it has been demonstrated experimentally in the wireless sensor network literature that the total energy consumption is often dominated by the communication cost, i.e. the computational and the sensing energy are small compared to the communication energy consumption. For this reason, the lifetime of the network can be extended significantly by minimizing the communication distance as well as the amount of communication data, at the expense of increasing computational cost. In this work, we aim at attaining an optimal trade-off between the communication and the computational energy. Specifically, we propose a mixed-integer optimization formulation for a multihop hierarchical clustering-based self-organizing UAV network incorporating data aggregation, to obtain an energy-efficient information routing scheme. The proposed framework is tested on two applications, namely target tracking and area mapping. Based on simulation results, our method can significantly save energy compared to a baseline strategy, where there is no data aggregation and clustering scheme
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