Graduate School and Research Center in Digital Sciences

Learning from the sky: Flying access networks for beyond 5G

Gesbert, David

WCSP 2017, Keynote Speech, 9th International Conference on Wireless Communications and Signal Processing, 11-13 October 2017, Nanjing, China

The use of flying robots (drones) carrying radio transceiver equipment is the new promising frontier in our quest towards ever more flexible, adaptable and spectrally efficient wireless networks. Beyond obvious challenges within regulatory, control, navigation, and operational domains, the deployment of autonomous flying radio access network (Fly-RANs) also come with a number of exciting new research problems such as the issue of optimal automatic placement of the drones in non-trivial propagation scenarios (i.e. scenarios where the optimal placement is not just dictated by a trivial geometry argument due to shadowing effects, e.g. in cities).  We present several different approaches, lying at the cross-roads between machine learning, signal processing and optimization. One approach involves the reconstruction of a city map from sampled radio measurements which can have application beyond the realm of communications.

Bibtex

Title:Learning from the sky: Flying access networks for beyond 5G
Type:Talk
Language:English
City:Nanjing
Country:CHINA
Date:
Department:Communication systems
Eurecom ref:5680
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Bibtex: @talk{EURECOM+5680, year = {2017}, title = {{L}earning from the sky: {F}lying access networks for beyond 5{G}}, author = {{G}esbert, {D}avid}, number = {EURECOM+5680}, month = {10}, institution = {Eurecom} address = {{N}anjing, {CHINA}}, url = {http://www.eurecom.fr/publication/5680} }
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