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PhD position Location Estimation @ EURECOM

3 Septembre 2021


Catégorie : Doctorant


 

Research topics

 

Geopositioning in IoT Networks

Department

Communication Systems Department, EURECOM

Publication date

08/2021

Start date

ASAP

Duration

duration of thesis

Web page

http://www.eurecom.fr/en/people/slock-dirk

Description

This PhD thesis contributes initially to the French FUI project GEOLOC, "Multi-Standard Geolocation for the Internet of Things",https://www.pole-scs.org/en/projects/geoloc-3/https://geoloc.univ-cotedazur.fr/?lang=fr

Background

According to the operators, a significant share of the applications of the Internet of Things (IoT) requires the geolocation (management of fleets of vehicles, applications related to the security in the broad sense,…). The geolocation of connected objects, in exterior and interior environments, and in particular its precision at a reduced cost (fabrication and energy consumption), is thus a major stake. The GEOLOC project proposes to study, develop and try out innovating techniques of multichannel geolocation estimation. The standards that will be used are both the standards using the free bands (LoRa, WiFi, Bluetooth low energy (WHEAT)) as well as the cellular technologies derived from 4G/5G.

Objectives

The GEOLOC project aims in particular:

  • To combine information from the various standards supported by an object (LoRa, LTE-M) but also (WHEAT, Wifi, GPS), as well as various sensors (barometer, accelerometer) to improve the precision of the geolocation (information fusion) while controlling consumption
  • In a way complementary to the primary goal, to improve the existing techniques of geolocation estimation
  • To use geolocation information to improve the effectiveness of the transmissions between the object and the infrastructure
  • To minimize the total consumption of the infrastructure and of the connected objects

Research Topics of this PhD thesis

An initial series of topics to be explored in this thesis includes:

  • Current GPS-based solutions are not optimized for IoT geolocation and mainly suffer from high power consumption, low accuracy in urban settings, and limited indoor coverage. Novel algorithms have been developed in order to overcome these drawbacks. With the help of the proposed signal processing solutions we are targeting to provide high accuracy and fast signal acquisition at low Line-of-Sight signal levels (e.g., behind buildings or indoor with signal strength 1,000 or 10,000 times weaker than in open, outdoor locations) or in the presence of signal reflections in urban environments (multipath). Further improvement and extensions of these algorithms are to be explored, for instance by exploiting multi-antenna reception.
  • One of the innovations envisaged concerns the use of multi-band signals (or frequency hopping or multi-standard). The ToA (Time of Arrival) resolution is inversely proportional to the signal bandwidth. So with the low bandwidth of IoT communications, the accuracy of distance measurement is a problem. In multi-band, if we receive in bands [

 

https://www.eurecom.fr/en/job/geopositioning-iot-networks