Cognitive Networks: Applications and Deployments download
Militano, G. Araniti, A. Orsino, A.
Martin, L. Dooley, K. Cognitive Radio Network Security. Contract-Based Secondary Spectrum Trading. Cooperation in Cognitive Cellular Heterogeneous Networks. Ahmed R. Elsherif, Hesham M.
Download Cognitive Networks : Applications And Deployments
Elmaghraby, Zhi Ding. Device-to-Device Communications over Unlicensed Spectrum. Improve TCO with innovative and agile use case creation, wide range of business and operational models and an open source, cloud native solution. Monetize insight and deliver on experience promise: Cognitive Analytics for Mobile Networks provides network intelligence for operations, planning, optimization, care and marketing serving a wide variety of use cases across enterprises, IoT and consumers.
14th EAI International Conference on Cognitive Radio Oriented Wireless Networks
Mobile broadband to home and consumers will require very high throughput whereas there will be a moderate number of devices served per cell. Vehicular communications will require ultra-low latency combined with fast mobility and handovers. Internet of Things and industrial robotics requires serving a huge number of devices but typically a low throughput per device. Typical use cases for Cognitive Analytics for Mobile Networks include the following:. The transformation to 5G passes through a new paradigm of network planning and implementation. In fact, 5G is a whole architecture change.
We also expect chapters addressing the pros and cons of specific proposals, and chapters addressing the key problems and solutions. The topics can be discussed in term of concepts, state of the art, standards, deployments, implementations, running experiments and applications. Authors should send the chapters in single column format single spaced, 10 point Times Roman font, 8. The maximum number of pages for the abstract is 2.
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