We develop a large number of software tools and hosting infrastructures to support the research developed at the Department. We will be detailing in this section the different tools available. You can take a look for the moment at the offer available within the UPF Knowledge Portal, the innovations created in the context of EU projects in the Innovation Radar and the software sections of some of our research groups:

 

 Artificial Intelligence

 Nonlinear Time Series Analysis

 Web Research 

 

 Music Technology

 Interactive  Technologies

 Barcelona MedTech

 Natural Language  Processing

 Nonlinear Time Series  Analysis

UbicaLab

Wireless Networking

Educational Technologies

GitHub

 

 

Back Wilhelmi F, Barrachina-Muñoz S, Bellalta B, Cano C, Jonsson A, Neu G. Potential and Pitfalls of Multi-Armed Bandits for Decentralized Spatial Reuse in WLANs. arXiv pre-print

Wilhelmi F, Barrachina-Muñoz S, Bellalta B, Cano C, Jonsson A, Neu G. Potential and Pitfalls of Multi-Armed Bandits for Decentralized Spatial Reuse in WLANs. arXiv pre-print

Spatial Reuse (SR) has recently gained attention for performance maximization in IEEE 802.11 Wireless Local Area Networks (WLANs). Decentralized mechanisms are expected to be key in the development of solutions for next-generation WLANs, since many deployments are characterized by being uncoordinated by nature. However, the potential of decentralized mechanisms is limited by the significant lack of knowledge with respect to the overall wireless environment. To shed some light on this subject, we show the main considerations and possibilities of applying online learning in uncoordinated WLANs for the SR problem. In particular, we provide a solution based on Multi-Armed Bandits (MABs) whereby independent WLANs dynamically adjust their frequency channel, transmit power and sensitivity threshold. To that purpose, we provide two different strategies, which refer to selfish and environment-aware learning. While the former stands for pure individual behavior, the second one aims to consider the performance experienced by surrounding nodes, thus taking into account the impact of individual actions on the environment. Through these two strategies, we delve into practical issues for enabling MABs usage in wireless networks, such as convergence ensuring or adversarial effects. In addition, our simulation results illustrate the potential of our proposed solutions for enabling SR in future WLANs, showing that substantial improvements on network performance are achieved regarding throughput and fairness.

https://arxiv.org/abs/1805.11083  

Additional material:

All of the source code used in this work is open under the GNU General Public License v3.0, encouraging sharing of algorithm between potential contributors.

Francesc Wilhelmi. Potentials and pitfalls of decentralized spatial reuse.

https:// github.com/fwilhelmi/potential_pitfalls_mabs_spatial_reuse Commit: e761e6e, 2018

The source code of 11axHDWLANSim is open under the GNU General Public License v3.0 and can be found at https://github.com/wn-upf/Komondo