389.174 Seminar Wireless Communications

Seminar Wireless Communications


Course No. 389.174 (TISS Link)
2019S, SE, 3.0h, 3.0EC

This year’s topic of the mobile communications seminar is focusing on mobility and hybrid cloud access as the enabler for wireless 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 concepts in which capacity will follow users movements and flows rather than coverage. Other new challenges are the support of remote radio locations, radio over fibre, relays in moving mass transportation and finding new data sources to track user flows in different direction. In this lecture, we will hear talks and work on paper on the how to reach these goals.


General Information

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 30.03.2019. 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.

The round of student talks will start after the easter holidays on Thursdays with 2-3 Students per session. A list of dates will be put online after paper registration.

Language: English

 Mode

The attendance of the seminar is compulsory! We will keep records of your attendance. The seminar starts with invited talks, after that the students give self prepared presentations (~30min). Each student has to prepare a written report that is due at the end of the semester (at latest June 15, 2019!) (~15pages).

The talks will take place on in June, more details will be announced in the course.

Beachten Sie beim Verfassen der Ausarbeitung bitte die Richtlinie der TU Wien zum Umgang mit Plagiaten: https://www.tuwien.ac.at/fileadmin/t/ukanzlei/Lehre_-_Leitfaden_zum_Umgang_mit_Plagiaten.pdf

Please consider the plagiarism guidelines of TU Wien when writing your seminar paper: http://www.tuwien.ac.at/fileadmin/t/ukanzlei/t-ukanzlei-english/Plagiarism.pdf

 

Hours per week: 3.0

 

Involved persons:

Univ.Prof. Peter Farkas,
Dr. Martin Slanina,
Univ.Prof. Markus Rupp,
+ invited researchers.

 


Dates:

Vorbesprechung: Donnerstag. 7.3.2019, 11:15 Uhr, in EI4

Meetings
7.3. Vienna – Meeting point at 11:30 @ EI4
  • Talk 1: Philipp Svoboda: “Beyond 5G, moving towards 6G”
14.3. Bratislava – Meeting point at 09:30 @ Main Train Station – platform 11 A-C  -Start at 11.10 meet in Velka aula
  • Talk1: Dr. Matus Turcsany from Ericsson agreed to have presentation: “5G:hype vs reality and what is beyond the initial release”
  • Talk2: tbd
21.3. Vienna – Meeting point at 12:00 @ EI2
  • Talk 1: Haris Gacanin (Department Head, Nokia Bell Labs):”Autonomous systems with active learning in wireless environment” by Haris Gačanin” http://www.infosys.tuwien.ac.at/news.html
  • Talk 2: Dr. Georg Löffelmann, (Head of Strategy, Innovation & Lifecycle A1 Telekom Austria AG) “5G und Regulierung aus Sicht eines MNO”
28.3. Brünn – Meeting point at 07:30 @ Main Train Station – BUS platform A-C (return leaving 13:40, 17:40)

Location: Technická 12, Brno, room TBD

This event will be part of the following workshop:

1st workshop on Interoperability of heterogenous RF systems

https://events.eventzilla.net/e/1st-workshop-on–interoperability-of-heterogenous-rf-systems-21387189

  • Seminar on Interoperability of heterogenous RF systems
    • Talk 1: Georg Brachtendorf from FH. Hagenberg
    • Talk 2: Holger Arthaber from TU Wien
4.4. Bratislava – Meeting point at 09:30 @ Main Train Station – platform 11 A-C  -Start at 11.10 meet in Velka aula
  • Talk 1: Dejan Vukobratovic: “From NB-IoT towards massive machine-type communications (mMTC) in 5G”
11.4. Brünn – Meeting point at 08:45 @ Main Train Station – BUS platform A-C (return leaving 13:40, 17:40)
  • Talk1: Miroslav Joler from University of Rijeka, Croatia : “Some Cases of Antenna Research for Modern Communications.”

Bring your travel documents.


 You might find this helpful: https://www.gcu.ac.uk/library/pilot/researchskills/criticalreviewing/
List of Papers (work in progress):
  1. Zhang, Y. Zeng, R. Zhang, “Cellular-Enabled UAV Communication: Trajectory Optimization Under Connec- tivity Constraint “,IEEE ICC, May 2018
  2. Roy V, et al. “Spatio-Temporal Field Estimation Using Kriged Kalman Filter (KKF) with Sparsity-Enforcing Sensor Placement.” Sensors, 2018
  3. Jing Wang et al, Spatiotemporal Modeling and Prediction in Cellular Networks: A Big Data Enabled Deep Learning Approach, INCOFCOM 17, 2017.
  4. [Urim Tafolli] Zang, F. Ni, Z. Feng, S. Cui, and Z. Ding, “Wavelet transform processing for cellular traffic prediction in machine learning networks,”
  5. [Jurgen Iliazi] Xu Wang, et al., Spatio-Temporal Analysis and Prediction of CellularTraffic in Metropolis, ICNP17, 2017.
  6. [Navid] Characterizing the Spatio-Temporal Inhomogeneity of Mobile Traffic in Large-scale Cellular Data Networks
  7. [Kirev, Kiril] Bowen Lu, et al. “Tracking and modeling of spatio-temporal fields with a mobile sensor network”, World Congress on Intelligent Control and Automation, 2014
  8. [Gerfried ?] Howard H. Yang, SIR Coverage Analysis in Cellular Networks with Temporal Traffic: A Stochastic Geometry Approach, submitted.
  9. Yi Zhong et al., Heterogeneous Cellular Networks with Spatio-Temporal Traffic: Delay Analysis and Scheduling, IEEE Journal on Selected Areas in Communications 2017.
  10. Chaoyun Zhang, Paul Patras, Long-Term Mobile Traffic Forecasting UsingDeep Spatio-Temporal Neural Networks,
  11. [Richard Pfister] Ben Said, et al, A Deep Learning Spatiotemporal PredictionFramework for Mobile Crowdsourced Services
  12. [Erjola Zeraliu] Chih-Wei Huang, et al. A Study of Deep Learning Networks onMobile Traffic Forecasting
  13. SIjia Liu, Sparsity-aware field estimation via ordinary Kriging, ICASSP 2014.

Legende: [Presenter] Paper