160 research outputs found

    Aerial base stations with opportunistic links for next generation emergency communications

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    Rapidly deployable and reliable mission-critical communication networks are fundamental requirements to guarantee the successful operations of public safety officers during disaster recovery and crisis management preparedness. The ABSOLUTE project focused on designing, prototyping, and demonstrating a high-capacity IP mobile data network with low latency and large coverage suitable for many forms of multimedia delivery including public safety scenarios. The ABSOLUTE project combines aerial, terrestrial, and satellites communication networks for providing a robust standalone system able to deliver resilience communication systems. This article focuses on describing the main outcomes of the ABSOLUTE project in terms of network and system architecture, regulations, and implementation of aerial base stations, portable land mobile units, satellite backhauling, S-MIM satellite messaging, and multimode user equipments

    Decentralized Spectrum Learning for IoT Wireless Networks Collision Mitigation

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    This paper describes the principles and implementation results of reinforcement learning algorithms on IoT devices for radio collision mitigation in ISM unlicensed bands. Learning is here used to improve both the IoT network capability to support a larger number of objects as well as the autonomy of IoT devices. We first illustrate the efficiency of the proposed approach in a proof-of-concept based on USRP software radio platforms operating on real radio signals. It shows how collisions with other RF signals present in the ISM band are diminished for a given IoT device. Then we describe the first implementation of learning algorithms on LoRa devices operating in a real LoRaWAN network, that we named IoTligent. The proposed solution adds neither processing overhead so that it can be ran in the IoT devices, nor network overhead so that no change is required to LoRaWAN. Real life experiments have been done in a realistic LoRa network and they show that IoTligent device battery life can be extended by a factor 2 in the scenarios we faced during our experiment

    Upper-Confidence Bound for Channel Selection in LPWA Networks with Retransmissions

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    In this paper, we propose and evaluate different learning strategies based on Multi-Arm Bandit (MAB) algorithms. They allow Internet of Things (IoT) devices to improve their access to the network and their autonomy, while taking into account the impact of encountered radio collisions. For that end, several heuristics employing Upper-Confident Bound (UCB) algorithms are examined, to explore the contextual information provided by the number of retransmissions. Our results show that approaches based on UCB obtain a significant improvement in terms of successful transmission probabilities. Furthermore, it also reveals that a pure UCB channel access is as efficient as more sophisticated learning strategies.Comment: The source code (MATLAB or Octave) used for the simula-tions and the figures is open-sourced under the MIT License, atBitbucket.org/scee\_ietr/ucb\_smart\_retran

    Designing and Implementing Future Aerial Communication Networks

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    Providing "connectivity from the sky" is the new innovative trend in wireless communications. High and low altitude platforms, drones, aircrafts and airships are being considered as the candidates for deploying wireless communications complementing the terrestrial communication infrastructure. In this article, we report the detailed account of the design and implementation challenges of an aerial network consisting of LTE Advanced (LTE-A) base stations. In particular, we review achievements and innovations harnessed by an aerial network composed of Helikite platforms. Helikites can be raised in the sky to bring Internet access during special events and in the aftermath of an emergency. The trial phase of the system mounting LTE-A technology onboard Helikites to serve users on the ground showed not only to be very encouraging but that such a system could offer even a longer lasting solution provided that inefficiency in powering the radio frequency equipment in the Helikite can be overcome.Comment: IEEE Communications Magazine 201

    Dynamic Spectrum Access Using OFDM-based Overlay Systems

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    A review of the use of artificial intelligence methods in infrastructure systems

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    The artificial intelligence (AI) revolution offers significant opportunities to capitalise on the growth of digitalisation and has the potential to enable the ‘system of systems’ approach required in increasingly complex infrastructure systems. This paper reviews the extent to which research in economic infrastructure sectors has engaged with fields of AI, to investigate the specific AI methods chosen and the purposes to which they have been applied both within and across sectors. Machine learning is found to dominate the research in this field, with methods such as artificial neural networks, support vector machines, and random forests among the most popular. The automated reasoning technique of fuzzy logic has also seen widespread use, due to its ability to incorporate uncertainties in input variables. Across the infrastructure sectors of energy, water and wastewater, transport, and telecommunications, the main purposes to which AI has been applied are network provision, forecasting, routing, maintenance and security, and network quality management. The data-driven nature of AI offers significant flexibility, and work has been conducted across a range of network sizes and at different temporal and geographic scales. However, there remains a lack of integration of planning and policy concerns, such as stakeholder engagement and quantitative feasibility assessment, and the majority of research focuses on a specific type of infrastructure, with an absence of work beyond individual economic sectors. To enable solutions to be implemented into real-world infrastructure systems, research will need to move away from a siloed perspective and adopt a more interdisciplinary perspective that considers the increasing interconnectedness of these systems
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