13,356 research outputs found

    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

    Network Topology and Time Criticality Effects in the Modularised Fleet Mix Problem

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    In this paper, we explore the interplay between network topology and time criticality in a military logistics system. A general goal of this work (and previous work) is to evaluate land transportation requirements or, more specifically, how to design appropriate fleets of military general service vehicles that are tasked with the supply and re-supply of military units dispersed in an area of operation. The particular focus of this paper is to gain a better understanding of how the logistics environment changes when current Army vehicles with fixed transport characteristics are replaced by a new generation of modularised vehicles that can be configured task-specifically. The experimental work is conducted within a well developed strategic planning simulation environment which includes a scenario generation engine for automatically sampling supply and re-supply missions and a multi-objective meta-heuristic search algorithm (i.e. Evolutionary Algorithm) for solving the particular scheduling and routing problems. The results presented in this paper allow for a better understanding of how (and under what conditions) a modularised vehicle fleet can provide advantages over the currently implemented system

    Low-complexity medium access control protocols for QoS support in third-generation radio access networks

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    One approach to maximizing the efficiency of medium access control (MAC) on the uplink in a future wideband code-division multiple-access (WCDMA)-based third-generation radio access network, and hence maximize spectral efficiency, is to employ a low-complexity distributed scheduling control approach. The maximization of spectral efficiency in third-generation radio access networks is complicated by the need to provide bandwidth-on-demand to diverse services characterized by diverse quality of service (QoS) requirements in an interference limited environment. However, the ability to exploit the full potential of resource allocation algorithms in third-generation radio access networks has been limited by the absence of a metric that captures the two-dimensional radio resource requirement, in terms of power and bandwidth, in the third-generation radio access network environment, where different users may have different signal-to-interference ratio requirements. This paper presents a novel resource metric as a solution to this fundamental problem. Also, a novel deadline-driven backoff procedure has been presented as the backoff scheme of the proposed distributed scheduling MAC protocols to enable the efficient support of services with QoS imposed delay constraints without the need for centralized scheduling. The main conclusion is that low-complexity distributed scheduling control strategies using overload avoidance/overload detection can be designed using the proposed resource metric to give near optimal performance and thus maintain a high spectral efficiency in third-generation radio access networks and that importantly overload detection is superior to overload avoidance

    Smart Grid Communications: Overview of Research Challenges, Solutions, and Standardization Activities

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    Optimization of energy consumption in future intelligent energy networks (or Smart Grids) will be based on grid-integrated near-real-time communications between various grid elements in generation, transmission, distribution and loads. This paper discusses some of the challenges and opportunities of communications research in the areas of smart grid and smart metering. In particular, we focus on some of the key communications challenges for realizing interoperable and future-proof smart grid/metering networks, smart grid security and privacy, and how some of the existing networking technologies can be applied to energy management. Finally, we also discuss the coordinated standardization efforts in Europe to harmonize communications standards and protocols.Comment: To be published in IEEE Communications Surveys and Tutorial
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