Cognitive Approaches for Location in Mobile environments

Project abstract

The most likely pillars of the future wireless society will be the trustability of the wireless positioning device (e.g., how much the user can get in terms of location accuracy, availability, privacy, etc.) and the eco-friendliness of the transmission-reception process (e.g., long battery life, power/energy saving devices and small power consumption, re-usable and modular blocks, high levels of integration, low interference to others, etc.). These are triggered by the user needs, preferences and targeted applications, as well as by the type of the environment where communication/navigation takes place (e.g., crowdiness of the spectrum, interference sources, channel dynamics, etc). There link between these user 'needs' and environment 'awareness' (or application layer) and the physical layer (where the wireless device is actually designed) can be built by the aid of cognitive approaches, borrowed on one hand from cognitive human behavior, and on the other hand from cognitive computing. The goals of CALM project have been to investigate and implement parts of this cognitive layer in a wireless location device, and to develop location software-defined radios based on cognitive signal processing.

Project details

The CALM project, together with its twin sisters CALM-rest I and CALM-rest II have been funded by the Academy of Finland, under the project numbers 250266, 256175, and 283076 and with a funding level of 677578 EUR over a five year duration (2011-2016).

External collaborators

The main research collaborators have been the SPCOMNAV group from Universitat Autonoma de Barcelona, Spain and Dept of Signal Processing and Acousticsfrom Aalto University, Finland. In addition, the team has collaborated and has joint publications with CITST (Romania) , Pildo Labs (Spain), SSAU (Rusia), Hanyang University,(South Korea), University Roma Tre (Italy).

Main results

  • Web-based extensive user surveys and analyses on user views on Location Based Services
  • Analysis of commercial services based on future GNSS systems
  • Derivation of quantitative indicators mapping user classes into users' preferences
  • Development of a unified cyclostationarity framework for GNSS type of signals
  • Algorithms for Signals of Opportunity (SoO) detection and identification
  • Statistical models of indoor path-loss propagation channels based on various SoO (such as cellular, WLAN, RFID, BLE)
  • Cooperative WLAN positioning studies
  • Novel statistical position estimators such as those based on Dempster-Shaffer theory