Nach positiver Absolvierung der Lehrveranstaltung sind Studierende in der Lage Kenntnisse der aktuellen Forschungsarbeiten und Entwicklungsarbeiten in der Mobilkommunikation, Vorbereitung auf erfolgreiche Tätigkeit bei österreichischer und europäischer Industrie bzw Netzbetreibern.

This year's topic of the mobile communications seminar is focusing on antennas as the enabler for wireless access networks of the future. 5G networks are expected to be significantly different from today's networks. The main requirements are: support up to 1000 times the capacity, reduce the latency of data delivery, flatten total energy consumption and finally make the network to be self-aware. These tasks will need new antennas designs in existing bands and completely new developments for the new spectra of 60GHz. Other new challenges are the support of remote radio locations, radio over fibre relays in moving mass transportation and finding new materials for the antenna itself to reduce the loss at very high frequencies. In this lecture, we will hear talks on how to reach these goals.

alle moderne methoden die gerade diskutiert werden können zur anwendung kommen

Note: 389.075 will not be offered anymore from 2017 on.

Note: Visiting the online course of the partner universities is a mandatorily required element of the seminar, make sure that you are able to join.

Note: This year the seminar will take place online.

The seminar starts on March 4 in Vienna online @ 13.00.

If you like to participate, please join at the date and contact

psvoboda@nt.tuwien.ac.at

check the homepage

https://www.nt.tuwien.ac.at/teaching/summer-term/389-174/

for recent information

the course is held in English. We will also travel to TU Bratislava as well as to TU Brno to attend the corresponding seminar over there. Attendence on these thrips is required.

Vorbesprechung: Donnerstag. 4.3., 12:30 Uhr, in Zoom

Zoom Link: https://tuwien.zoom.us/j/97241397442?pwd=RDdRL1pLY2tLb1dTem55dEQzRm8xQT09

Meetings 4.3. Vienna - Meeting point Zoom (https://tuwien.zoom.us/j/97241397442?pwd=RDdRL1pLY2tLb1dTem55dEQzRm8xQT09) @ 13.00

• Introduction to 5G Simulator (Recorded Session), Prof. Kaltenberger (EURECOM)

11.3. Bratislava - Meeting Point Zomm (see above) 13.00 (2h)

• Virtualized RAN as a service; Ing. Martin Macuha, PhD. Technology Consulting Manager at Accenture

18.3. Bratislava - Meeting Point Zomm (see above) 13.00 (2h)

• ORAN perspectives Ing. Matú Turcsány, PhD., Chief Technology Officer (Czech, Hungary, Slovakia, Slovenia) Ericsson.

25.3. Vienna - Meeting point Zoom (see above)  @ 13.00 (3h)

• 13.00 Elmar Trojer (Ericsson Research)

• 14.00 David Gesbert (EURECOM)

8.4. Brno - Meeting point Zoom (see above)  @ 9.30 -- 11.30 (2h)

• ing. Michal Pokorný, Ph.D. (Resideo)

15.4. Brno - Meeting point Zoom (see above)  @ 9.00 -- 11.00 (+discussion) (2h)

• RF engineering for advanced satellite telecommunication payloads ing. Václav Valenta, Ph.D. (ESA)

In the first part of the seminar, university researchers present their latest research in their field in 5G and new applications as well as challenges for 5G.

In the second part of the seminar, students will read literature and research papers on antenna systems for 5G and reflect their results by their own presentations. Please choose one paper from our suggested paper list and report to Philipp Svoboda till 30.03.2021. Papers will be assigned on a first-come-first-serve basis. Note: you can also bring your own topic/paper, the list is only a suggestion.

List of Papers (work in progress):

1. Chen, Y., Lin, X., Khan, T., & Mozaffari, M. (2019). Efficient drone mobility support using reinforcement learning. ArXiv, 2–7.
2. Hu, Y., Chen, M., Saad, W., Poor, H. V., & Cui, S. (2020). Distributed Multi-agent Meta Learning for Trajectory Design in Wireless Drone Networks, 1–31. Retrieved from http://arxiv.org/abs/2012.03158
3. Dai, A., Li, R., Zhao, Z., & Zhang, H. (2020). Graph Convolutional Multi-Agent Reinforcement Learning for UAV Coverage Control, 1106–1111. https://doi.org/10.1109/wcsp49889.2020.9299760
4. Cao, Y., Lien, S. Y., & Liang, Y. C. (2020). Deep Reinforcement Learning For Multi-User Access Control in Non-Terrestrial Networks. IEEE Transactions on Communications, 6778(c), 1–15. https://doi.org/10.1109/TCOMM.2020.3041347
5. Liu, C. H., Ma, X., Gao, X., & Tang, J. (2020). Distributed Energy-Efficient Multi-UAV Navigation for Long-Term Communication Coverage by Deep Reinforcement Learning. IEEE Transactions on Mobile Computing, 19(6), 1274–1285. https://doi.org/10.1109/TMC.2019.2908171
6. Gama, F., Isufi, E., Leus, G., & Ribeiro, A. (2020). Graphs, Convolutions, and Neural Networks, (November).
7. Wu, M., & Li, C. (2020). 5G Wireless Intelligent Propagation Channel Modelling Based on Deep Residual Network. Proceedings – 2020 2nd International Conference on Advances in Computer Technology, Information Science and Communications, CTISC 2020, 64–70. https://doi.org/10.1109/CTISC49998.2020.00017
8. Li, T., Zhu, X., & Liu, X. (2020). An End-to-End Network Slicing Algorithm Based on Deep Q-Learning for 5G Network. IEEE Access, 8, 122229–122240. https://doi.org/10.1109/ACCESS.2020.3006502
9. Lv, Z., Qiao, L., & You, I. (2020). 6G-Enabled Network in Box for Internet of Connected Vehicles. IEEE Transactions on Intelligent Transportation Systems, 1–8. https://doi.org/10.1109/tits.2020.3034817
10. Shafin, R., Liu, L., Chandrasekhar, V., Chen, H., Reed, J., & Zhang, J. C. (2019). Artificial intelligence-enabled cellular networks: A critical path to beyond-5G and 6G. ArXiv, (April), 212–217.
11. Sliwa, B., Falkenberg, R., & Wietfeld, C. (2020). Towards Cooperative Data Rate Prediction for Future Mobile and Vehicular 6G Networks. ArXiv, 6–10.
12. Forward, C., Bandwidth, E., & Access, M. (2020). Machine Learning for 6G Wireless, (September), 2–14.

This seminar is targeted for students in the Master of telecommunications. Note that the seminar requires travelling to bratislava and brno and is held entirely in english