2,048 research outputs found
Thirty Years of Machine Learning: The Road to Pareto-Optimal Wireless Networks
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
Software Defined Networks based Smart Grid Communication: A Comprehensive Survey
The current power grid is no longer a feasible solution due to
ever-increasing user demand of electricity, old infrastructure, and reliability
issues and thus require transformation to a better grid a.k.a., smart grid
(SG). The key features that distinguish SG from the conventional electrical
power grid are its capability to perform two-way communication, demand side
management, and real time pricing. Despite all these advantages that SG will
bring, there are certain issues which are specific to SG communication system.
For instance, network management of current SG systems is complex, time
consuming, and done manually. Moreover, SG communication (SGC) system is built
on different vendor specific devices and protocols. Therefore, the current SG
systems are not protocol independent, thus leading to interoperability issue.
Software defined network (SDN) has been proposed to monitor and manage the
communication networks globally. This article serves as a comprehensive survey
on SDN-based SGC. In this article, we first discuss taxonomy of advantages of
SDNbased SGC.We then discuss SDN-based SGC architectures, along with case
studies. Our article provides an in-depth discussion on routing schemes for
SDN-based SGC. We also provide detailed survey of security and privacy schemes
applied to SDN-based SGC. We furthermore present challenges, open issues, and
future research directions related to SDN-based SGC.Comment: Accepte
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LTE-Advanced radio access enhancements: A survey
Long Term Evolution Advanced (LTE-Advanced) is the next step in LTE evolution and allows operators to improve network performance and service capabilities through smooth deployment of new techniques and technologies. LTE-Advanced uses some new features on top of the existing LTE standards to provide better user experience and higher throughputs. Some of the most significant features introduced in LTE-Advanced are carrier aggregation, enhancements in heterogeneous networks, coordinated multipoint transmission and reception, enhanced multiple input multiple output usage and deployment of relay nodes in the radio network. Mentioned features are mainly aimed to enhance the radio access part of the cellular networks. This survey article presents an overview of the key radio access features and functionalities of the LTE-Advanced radio access network, supported by the simulation results. We also provide a detailed review of the literature together with a very rich list of the references for each of the features. An LTE-Advanced roadmap and the latest updates and trends in LTE markets are also presented
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