1,757 research outputs found

    Spectrum Trading: An Abstracted Bibliography

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    This document contains a bibliographic list of major papers on spectrum trading and their abstracts. The aim of the list is to offer researchers entering this field a fast panorama of the current literature. The list is continually updated on the webpage \url{http://www.disp.uniroma2.it/users/naldi/Ricspt.html}. Omissions and papers suggested for inclusion may be pointed out to the authors through e-mail (\textit{[email protected]})

    Spectrum Sharing Optimization and Analysis in Cellular Networks under Target Performance and Budget Restriction

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    Dynamic Spectrum Sharing (DSS) aims to provide opportunistic access to under-utilised spectrum in cellular networks for secondary network operators. In this paper we propose an algorithm using stochastic and optimisation models to borrow spectrum bandwidths under the assumption that more resources exist for secondary access than the secondary network demand by considering a merchant mode. The main aim of the paper is to address the problem of spectrum borrowing in DSS environments, where a secondary network operator aims to borrow the required spectrum from multiple primary network operators to achieve a maximum profit under specific grade of service (GoS) and budget restriction. We assume that the primary network operators offer spectrum access opportunities with variable number of channels (contiguous and/or non-contiguous) at variable prices. Results obtained are then compared with results derived from an algorithm in which spectrum borrowing are random. Comparisons showed that the gain in the results obtained from our proposed stochastic-optimisation framework is significantly higher than random counterpart

    Feasibility, Architecture and Cost Considerations of Using TVWS for Rural Internet Access in 5G

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    The cellular technology is mostly an urban technology that has been unable to serve rural areas well. This is because the traditional cellular models are not economical for areas with low user density and lesser revenues. In 5G cellular networks, the coverage dilemma is likely to remain the same, thus widening the rural-urban digital divide further. It is about time to identify the root cause that has hindered the rural technology growth and analyse the possible options in 5G architecture to address this issue. We advocate that it can only be accomplished in two phases by sequentially addressing economic viability followed by performance progression. We deliberate how various works in literature focus on the later stage of this ‘two-phase’ problem and are not feasible to implement in the first place. We propose the concept of TV band white space (TVWS) dovetailed with 5G infrastructure for rural coverage and show that it can yield cost-effectiveness from a service provider’s perspective

    A survey on intelligent computation offloading and pricing strategy in UAV-Enabled MEC network: Challenges and research directions

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    The lack of resource constraints for edge servers makes it difficult to simultaneously perform a large number of Mobile Devices’ (MDs) requests. The Mobile Network Operator (MNO) must then select how to delegate MD queries to its Mobile Edge Computing (MEC) server in order to maximize the overall benefit of admitted requests with varying latency needs. Unmanned Aerial Vehicles (UAVs) and Artificial Intelligent (AI) can increase MNO performance because of their flexibility in deployment, high mobility of UAV, and efficiency of AI algorithms. There is a trade-off between the cost incurred by the MD and the profit received by the MNO. Intelligent computing offloading to UAV-enabled MEC, on the other hand, is a promising way to bridge the gap between MDs' limited processing resources, as well as the intelligent algorithms that are utilized for computation offloading in the UAV-MEC network and the high computing demands of upcoming applications. This study looks at some of the research on the benefits of computation offloading process in the UAV-MEC network, as well as the intelligent models that are utilized for computation offloading in the UAV-MEC network. In addition, this article examines several intelligent pricing techniques in different structures in the UAV-MEC network. Finally, this work highlights some important open research issues and future research directions of Artificial Intelligent (AI) in computation offloading and applying intelligent pricing strategies in the UAV-MEC network

    Resource Management in Converged Optical and Millimeter Wave Radio Networks: A Review

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    Three convergent processes are likely to shape the future of the internet beyond-5G: The convergence of optical and millimeter wave radio networks to boost mobile internet capacity, the convergence of machine learning solutions and communication technologies, and the convergence of virtualized and programmable network management mechanisms towards fully integrated autonomic network resource management. The integration of network virtualization technologies creates the incentive to customize and dynamically manage the resources of a network, making network functions, and storage capabilities at the edge key resources similar to the available bandwidth in network communication channels. Aiming to understand the relationship between resource management, virtualization, and the dense 5G access and fronthaul with an emphasis on converged radio and optical communications, this article presents a review of how resource management solutions have dealt with optimizing millimeter wave radio and optical resources from an autonomic network management perspective. A research agenda is also proposed by identifying current state-of-the-art solutions and the need to shift all the convergent issues towards building an advanced resource management mechanism for beyond-5G
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