direkt zum Inhalt springen

direkt zum Hauptnavigationsmenü

Sie sind hier

TU Berlin

Inhalt des Dokuments

Miguel Angel Gutierrez

Miguel Angel Gutierrez


Miguel A. Gutierrez-Estevez received the Engineering degree in telecommunications from Universidad de Granada, Spain, in 2012. He is currently working toward the Ph.D. degree since 2013 with the Signal and Information Theory group in the Fraunhofer Heinrich-Herz Institute (HHI) in Berlin, Germany, under the supervision of Prof. Slawomir Stanczak on the topic of distributed systems for 5G networks. He joint the HHI in 2009 first as a Research Assistant and since 2012 as a Research Associate. His current interests are acoustic communications for challenging environments, signal processing for distributed systems and optimization in wireless systems.


Find me also


Online Learning of Any-to-Any Path Loss Maps
Citation key Guti2021onlearn
Author M. A. Gutierrez-Estevez, M. Kasparick and S. Stanczak
Year 2021
Journal IEEE Communications Letters
Editor IEEE
Abstract Learning any-to-any (A2A) path loss maps might be a key enabler for many applications that rely on a device-todevice (D2D) communication, such as vehicle-to-vehicle (V2V) communications. Current approaches for learning A2A maps have a number of important limitations, including i) a high complexity that increases rapidly with the number of samples, making the problems quickly intractable, and ii) the inability of coping with a time-varying environment, among others. In this paper, we propose a novel approach that reconstruct A2A path loss maps in an online fashion. To that end, we leverage on the framework of stochastic learning to deal with the sequential arrival of samples, and propose an online algorithm based on the forward-backward splitting method. Preliminary simulation results show a significant decrease in complexity, while its performance is comparable to that of a batch approach.
Download Bibtex entry

Zusatzinformationen / Extras

Quick Access:

Schnellnavigation zur Seite über Nummerneingabe

Auxiliary Functions

This site uses Matomo for anonymized web analytics. More information and opt-out options under data protection.