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Data Analytics in Wireless Networks

 

Due to the heterogeneity of ubiquitous wireless systems, which may be found in populated areas, there is a growing interest in data analytics and network configurations that open up a range of new possibilities and applications with the forthcoming ecosystem of the wireless technologies. Toward this goal, our research line deals with RF-based positioning techniques, IoT networks, machine learning tools in wireless systems and, spectrum sharing strategies.

Expertise

IoT networks:

  • IoT network planning.
    • Efficient deployment and dimensioning.
    • Coverage in IoT LPWA networks.
  • New paradigms of coordinated management and cooperation in massive IoT systems.
    • Network management and optimization.
    • Massive data collection.
  • Implementation on LPWA network development kits.

RF-based positioning and activity detection:

  • Non-intrusive detection of people in WiFi networks.
  • Machine learning techniques in expert systems.

Cognitive radio and spectrum sharing:

    • Development of spectrum sensing algorithms: adaptive techniques, cooperative networks.
    • Development of spectrum access strategies: licensed shared access, opportunistic access, databases and radio environment maps.
    • Prototype implementation with software-defined radio (SDR) frameworks.

EHUCOUNT Dataset:

Wi-Fi CSI Dataset for device-free counting people according to:

I. Sobron, J. Del Ser, I. Eizmendi and M. Vélez, "Device-Free People Counting in IoT Environments: New Insights, Results, and Open Challenges," in IEEE Internet of Things Journal, vol. 5, no. 6, pp. 4396-4408, Dec. 2018. doi: 10.1109/JIOT.2018.2806990

The following dataset consists of a zip file which contains a README text file and six mat files compatible with MATLAB and OCTAVE.

Download here

TSR group attends different events. Click here for more information.

TSR group members have made several international research stays in multiple countries. Click here for more information.