CROWNCOM 2020 - 15th EAI International Conference on Cognitive Radio Oriented Wireless Networks

EAI CROWNCOM 2020


Computer Networks & Wireless Communication



Scope
The aim of CROWNCOM 2020 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.
Moving from the wider scope embraced in the last edition, the main scope of CROWNCOM 2020 is on the intersection and interaction between cognition and communications in the context of 5G networks and beyond. Cognitive Radio included since its original definition concepts that go beyond the specific aspects of radio flexibility, dynamic spectrum access, and efficient spectrum sharing, that constituted the core research topics on Cognitive Radio in its early years. The new 5G paradigm and its expected evolutions into 6G and beyond led however to increased interest in the wider role that cognition can play in increasing system flexibility through access to rich context information, leading to the explosion of research and industry proposals to introduce additional intelligence in networks, typically by means of machine learning and big data analysis.
In this context, CROWNCOM 2020 will encompass all research aspects related to 5G and beyond systems that may benefit from the introduction of cognitive mechanisms, as well as communication algorithms, protocols and technologies that can enable the introduction and efficient deployment of such mechanisms. Contributions focusing on research advances, examples of state-of-the-art industrial deployments and contributions to standards and policies will be welcome, in order to ensure cross-contamination between all the communities historically involved in CROWNCOM.
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Topics
CROWNCOM 2020 invites submissions of research results and position papers on the following topics of interest, but not limited to:
- Machine learning algorithms and solutions for 5G and beyond
- Usage of Context Information in future wireless system
- Spectrum and resource virtualization
- Spectrum, infrastructure and resource management in future wireless networks
- New applications of cognitive radio based technologies in future wireless networks
- Deep learning and data mining in wireless networks
- Spectrum sharing and cognitive networks, including DSA, LSA, LAA, CBRS-SAS
- Coexistence in unlicensed bands (including offload mechanisms)
- Cognitive Radio Related Standards and initiatives
- Spectrum efficiency optimisation at any layer level perspective (at PHY, MAC, networking and application level)
- Radio resource slicing and radio virtualization techniques
- Spectrum for digital inclusion
- Application of cognitive radio and sharing for the IoT
- Cognitive radio technology for V2V and V2X applications
- Sharing and coexistence in mmWave bands and satellite communications
- Experimental results on spectrum efficiency of end-to-end wireless systems and trials
- Spectrum sharing and security
- Business aspects and new opportunities related to spectrum sharing models and deployments
- Fundamentals of cognitive radio, e.g., advances in spectrum sensing, dynamic spectrum access
- RAN Slicing
- Heterogeneous network coexistence
- Spectrum usage in high frequency bands (mmWave, VLC, THz)
- Backhauling aspects in future networks
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Publication
All registered papers will be submitted for publication by Springer and made available through SpringerLink Digital Library.
Proceedings will be submitted for inclusion in leading indexing services, including Ei Compendex, ISI Web of Science, Scopus, CrossRef, Google Scholar, DBLP, as well as EAI’s own EU Digital Library (EUDL).
All accepted authors are eligible to submit an extended version in a fast track of:
- EAI Endorsed Transactions on Cognitive Communications
- EAI Endorsed Transactions on Wireless Spectrum
Additional publication opportunities:
- EAI Transactions series (Open Access)
- EAI/Springer Innovations in Communications and Computing Book Series