101 research outputs found

    Mobility performance of macrocell-assisted small cells in Manhattan model

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    Macrocell-assisted small cell concepts, such as "Phantom cell concept" and "soft cell concept", have been proposed previously for interference management, flexible cell planning, and energy saving in dense small cell deployments. These concepts require macrocell involvement to improve links between small cell and user. Since target implementation areas of the concepts are crowded urban areas (e.g. downtown New York City) to satisfy the data need, more realistic simulations are needed to be implemented compared to conventional evaluations. In this paper, as a new approach to urban area LTE simulations, Manhattan grid layout is presented and implemented for mobility performance of Macrocell-assisted small Cell concept. The results show that the macrocell involvement to improve mobility performance gives a great advantage compared to using the conventional mobility solution for dense small cell deployments

    Data-Driven Handover Optimization in Next Generation Mobile Communication Networks

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    Ubiquitous wi-fi implementations in hotels: Key planning factors

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    The Internet has changed the way in which people work and live. Many when traveling expect to be Internet-connected at all times without being tied down to physical wires, just as in their offices and homes. Wireless Fidelity (Wi-Fi) enables hotel guests with wireless-capable computers and devices to easily access high speed broadband networks within the coverage area. According to J.D. Power and Associates North America Hotel Guest Satisfaction Index Study, hotels that provide fast, reliable Internet service receive high ratings from guests. Wi-Fi, initially deployed in public spaces, is now an expected room amenity. Providing reliable and robust Wi-Fi coverage throughout a hotel requires careful implementation planning for technical as well as business-related factors. This article identifies and discusses key Wi-Fi planning factors and their implications for wireless network architecture decisions in hotel environments

    Thirty Years of Machine Learning: The Road to Pareto-Optimal Wireless Networks

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    Future wireless networks have a substantial potential in terms of supporting a broad range of complex compelling applications both in military and civilian fields, where the users are able to enjoy high-rate, low-latency, low-cost and reliable information services. Achieving this ambitious goal requires new radio techniques for adaptive learning and intelligent decision making because of the complex heterogeneous nature of the network structures and wireless services. Machine learning (ML) algorithms have great success in supporting big data analytics, efficient parameter estimation and interactive decision making. Hence, in this article, we review the thirty-year history of ML by elaborating on supervised learning, unsupervised learning, reinforcement learning and deep learning. Furthermore, we investigate their employment in the compelling applications of wireless networks, including heterogeneous networks (HetNets), cognitive radios (CR), Internet of things (IoT), machine to machine networks (M2M), and so on. This article aims for assisting the readers in clarifying the motivation and methodology of the various ML algorithms, so as to invoke them for hitherto unexplored services as well as scenarios of future wireless networks.Comment: 46 pages, 22 fig

    Patient Safety and Quality: An Evidence-Based Handbook for Nurses

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    Compiles peer-reviewed research and literature reviews on issues regarding patient safety and quality of care, ranging from evidence-based practice, patient-centered care, and nurses' working conditions to critical opportunities and tools for improvement

    Toward Effective Physical Human-Robot Interaction

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    With the fast advancement of technology, in recent years, robotics technology has significantly matured and produced robots that are able to operate in unstructured environments such as domestic environments, offices, hospitals and other human-inhabited locations. In this context, the interaction and cooperation between humans and robots has become an important and challenging aspect of robot development. Among the various kinds of possible interactions, in this Ph.D. thesis I am particularly interested in physical human-robot interaction (pHRI). In order to study how a robot can successfully engage in physical interaction with people and which factors are crucial during this kind of interaction, I investigated how humans and robots can hand over objects to each other. To study this specific interactive task I developed two robotic prototypes and conducted human-robot user studies. Although various aspects of human-robot handovers have been deeply investigated in the state of the art, during my studies I focused on three issues that have been rarely investigated so far: Human presence and motion analysis during the interaction in order to infer non-verbal communication cues and to synchronize the robot actions with the human motion; Development and evaluation of human-aware pro-active robot behaviors that enable robots to behave actively in the proximity of the human body in order to negotiate the handover location and to perform the transfer of the object; Consideration of objects grasp affordances during the handover in order to make the interaction more comfortable for the human
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