Dynamic Spectrum Management: the 5G Verticals view
At the verge of 5G network deployment, new important stakeholders are more and more emerging as key users and customers of 5G systems, the so called 5G Verticals.
New spectrum bands for 5G usage are being or are going to be auctioned and new opportunities will therefore arise for both spectrum incumbents and new players in the 5G scene.
If, in addition to the new spectrum bands, one considers also a more dynamic usage of spectrum, which additional new opportunities are going to be created for the wireless ecosystem business?
This panel cluster experts from both the research domain and the industry, to address, above other topics, the above mentioned question.
The panel starts with a few short presentations focusing on some key points, which highlight the need for more dynamicity in the spectrum management of the forthcoming 5G networks.
After the presentations, a set of questions will be asked to the panel participants, and then the floor is open to the audience, with the final aim of establishing a live and open conversation between all the panel participants and attendees.
The panel lasts 70 minutes and is organized and led by Dr. Valerio Frascolla (Intel Deutschland), who is honored to host the following panelists, some of which talk about a specific vertical topic of interest:
1. Gasan Noh (ETRI, KR), talk on "Spectrum issues in satellite and cellular integration"
2. Johann Marquez-Barja (IMEC, BE), talk on “Smart usage of the spectrum within Smart Cities”
3. Andreas Wilzeck (Sennheiser, DE), talk on “Spectrum for Local Area 5G Networks in a Perspective of Culture and Creative Industries”
4. Jaeweon Kim (National Instrument, US).
Machine Learning in Wireless Networks
Communication networks are always facing dynamic and complex environments. Current communication algorithms and protocols are struggling to provide comprehensive, robust and scalable solutions. This is especially true for dynamic spectrum access networks where the radio environments are extremely complicated. On the other hand, machine learning is shown to be able to provide new opportunities and solution techniques for communication networks and systems.
This panel cluster experts from the industry, the government, and the academia to explore questions, challenges and promises of machine learning in wireless communications: Where do we see are the major opportunities for machine learning for wireless communication systems especially dynamic spectrum access networks? What are good target areas and problems in wireless communications that are suitable for machine learning techniques? Where do we see are the major opportunities for machine learning in 5G since 5G is still designed using conventional approaches?
The panel starts with a few short presentations focusing on some key points for machine learning for wireless communications. After the presentations, a set of questions will be asked to the panel participants, and then the floor is open to the audience, with the final aim of establishing a live and open conversation between all the panel participants and attendees.
The panel lasts 70 minutes and is organized and led by Dr. Lingjia Liu (Virginia Tech).
1. Paul Tilghman (DARPA, USA)
2. Lizhong Zheng (MIT, USA)
3. Juho Lee (moderator) (Samsung Electronics, Korea)
4. Jong-sik Lee (KT, Korea)