CROWNCOM 2019! 14TH EAI INTERNATIONAL CONFERENCE ON COGNITIVE RADIO ORIENTED WIRELESS NETWORKS

April 17th, 2019 Daniela Lopez de Luise

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June 11-12, 2019 | Poznan, Poland
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Scope
The aim of CROWNCOM 2019 is to bring together researchers and experts from academia, industry, standards, and policy to present their new solutions of how cognitive radio systems will help deliver the required stringent requirements of future 5G and beyond 5G networks. Following the success of last edition, the main scope of this event is on new application domains for the cognitive-based solutions in the context of 5G and beyond. In particular we will concentrate on science and industry drivers such as machine learning and big data analysis in future wireless networks.
Various aspects originated form Cognitive Radio domain, such as dynamic spectrum access, increased system flexibility through access to rich context information, spectrum sharing, virtualization and management, have been considered for application in various context. The emergence of 5G raised unprecedented expectations in terms of broadband services, latency and convergence of broadband systems with IoT networks. In this context, CROWNCOM 2019 will encompass a large scope of research topic also covering IoT in 5G and how cognitive mechanisms shall help leveraging access for billions of devices ; mmWave and how specific propagation and operation in these bands bring new sharing mechanisms ; how resource allocation amongst bands (including offload mechanisms) shall be solved. The key focus will be on how can rich data analysis improve the delivery of above defined services.
List of the included topics can be found here.
We are pleased to invite you to attend CROWNCOM, which will take place in Poznan, Poland on JUNE 11-12 2019.  

Keynote Speakers
Dr. Stefan Parkvall

5G NR – The Next Generation Wireless Access

Marcin Dryjanski

 Why “one-size-fits-all” approach does not work anymore?

Tutorial

This tutorial will shed light on the challenges, solutions and technologies, and enabling tools focusing on opensource tools to realize network slicing with data-driven control in 5G leveraging machine learning (ML) techniques. Particularly, the tutorial will also rely on concrete prototypes and solutions with alternative RAN slicing and control approaches to assess how the performance guarantee and isolation properties are provided to each slice and how the runtime control is used to optimize the network and service objectives.

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