233 research outputs found

    Coexistence of OFDM and FBMC for Underlay D2D Communication in 5G Networks

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    Device-to-device (D2D) communication is being heralded as an important part of the solution to the capacity problem in future networks, and is expected to be natively supported in 5G. Given the high network complexity and required signalling overhead associated with achieving synchronization in D2D networks, it is necessary to study asynchronous D2D communications. In this paper, we consider a scenario whereby asynchronous D2D communication underlays an OFDMA macro-cell in the uplink. Motivated by the superior performance of new waveforms with increased spectral localization in the presence of frequency and time misalignments, we compare the system-level performance of a set-up for when D2D pairs use either OFDM or FBMC/OQAM. We first demonstrate that inter-D2D interference, resulting from misaligned communications, plays a significant role in clustered D2D topologies. We then demonstrate that the resource allocation procedure can be simplified when D2D pairs use FBMC/OQAM, since the high spectral localization of FBMC/OQAM results in negligible inter-D2D interference. Specifically, we identify that FBMC/OQAM is best suited to scenarios consisting of small, densely populated D2D clusters located near the encompassing cell's edge.Comment: 7 pages, 9 figures, Accepted at IEEE Globecom 2016 Workshop

    Device-to-Device Communication in 5G Cellular Networks

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    Owing to the unprecedented and continuous growth in the number of connected users and networked devices, the next-generation 5G cellular networks are envisaged to support enormous number of simultaneously connected users and devices with access to numerous services and applications by providing networks with highly improved data rate, higher capacity, lower end-to-end latency, improved spectral efficiency, at lower power consumption. D2D communication underlaying cellular networks has been proposed as one of the key components of the 5G technology as a means of providing efficient spectrum reuse for improved spectral efficiency and take advantage of proximity between devices for reduced latency, improved user throughput, and reduced power consumption. Although D2D communication underlaying cellular networks promises lots of potentials, unlike the conventional cellular network architecture, there are new design issues and technical challenges that must be addressed for proper implementation of the technology. These include new device discovery procedures, physical layer architecture and radio resource management schemes. This thesis explores the potentials of D2D communication as an underlay to 5G cellular networks and focuses on efficient interference management solutions through mode selection, resource allocation and power control schemes. In this work, a joint admission control, resource allocation, and power control scheme was implemented for D2D communication underlaying 5G cellular networks. The performance of the system was evaluated, and comparisons were made with similar schemes.fi=Opinnäytetyö kokotekstinä PDF-muodossa.|en=Thesis fulltext in PDF format.|sv=Lärdomsprov tillgängligt som fulltext i PDF-format

    Security for 5G Mobile Wireless Networks

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    The advanced features of 5G mobile wireless network systems yield new security requirements and challenges. This paper presents a comprehensive survey on security of 5G wireless network systems compared to the traditional cellular networks. The paper starts with a review on 5G wireless networks particularities as well as on the new requirements and motivations of 5G wireless security. The potential attacks and security services with the consideration of new service requirements and new use cases in 5G wireless networks are then summarized. The recent development and the existing schemes for the 5G wireless security are presented based on the corresponding security services including authentication, availability, data confidentiality, key management and privacy. The paper further discusses the new security features involving different technologies applied to 5G such as heterogeneous networks, device-to-device communications, massive multiple-input multiple-output, software defined networks and Internet of Things. Motivated by these security research and development activities, we propose a new 5G wireless security architecture, based on which the analysis of identity management and flexible authentication is provided. As a case study, we explore a handover procedure as well as a signaling load scheme to show the advantage of the proposed security architecture. The challenges and future directions of 5G wireless security are finally summarized

    A review on green caching strategies for next generation communication networks

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    © 2020 IEEE. In recent years, the ever-increasing demand for networking resources and energy, fueled by the unprecedented upsurge in Internet traffic, has been a cause for concern for many service providers. Content caching, which serves user requests locally, is deemed to be an enabling technology in addressing the challenges offered by the phenomenal growth in Internet traffic. Conventionally, content caching is considered as a viable solution to alleviate the backhaul pressure. However, recently, many studies have reported energy cost reductions contributed by content caching in cache-equipped networks. The hypothesis is that caching shortens content delivery distance and eventually achieves significant reduction in transmission energy consumption. This has motivated us to conduct this study and in this article, a comprehensive survey of the state-of-the-art green caching techniques is provided. This review paper extensively discusses contributions of the existing studies on green caching. In addition, the study explores different cache-equipped network types, solution methods, and application scenarios. We categorically present that the optimal selection of the caching nodes, smart resource management, popular content selection, and renewable energy integration can substantially improve energy efficiency of the cache-equipped systems. In addition, based on the comprehensive analysis, we also highlight some potential research ideas relevant to green content caching

    D3.2 First performance results for multi -node/multi -antenna transmission technologies

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    This deliverable describes the current results of the multi-node/multi-antenna technologies investigated within METIS and analyses the interactions within and outside Work Package 3. Furthermore, it identifies the most promising technologies based on the current state of obtained results. This document provides a brief overview of the results in its first part. The second part, namely the Appendix, further details the results, describes the simulation alignment efforts conducted in the Work Package and the interaction of the Test Cases. The results described here show that the investigations conducted in Work Package 3 are maturing resulting in valuable innovative solutions for future 5G systems.Fantini. R.; Santos, A.; De Carvalho, E.; Rajatheva, N.; Popovski, P.; Baracca, P.; Aziz, D.... (2014). D3.2 First performance results for multi -node/multi -antenna transmission technologies. http://hdl.handle.net/10251/7675

    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
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