Alyafawi, Islam (2012). Towards Self-Learning Radio-Based Localization Systems. In: IEEE International Conference on Pervasive Computing and Communications Workshops PERCOM PhD Forum, Lugano, Switzerland (pp. 556-557). IEEE 10.1109/PerComW.2012.6197572
Full text not available from this repository. (Request a copy)Location-awareness indoors will be an inseparable feature of mobile services/applications in future wireless networks. Its current ubiquitous availability is still obstructed by technological challenges and privacy issues. We propose an innovative approach towards the concept of indoor positioning with main goal to develop a system that is self-learning and able to adapt to various radio propagation environments. The approach combines estimation of propagation conditions, subsequent appropriate channel modelling and optimisation feedback to the used positioning algorithm. Main advantages of the proposal are decreased system set-up effort, automatic re-calibration and increased precision.
Item Type: |
Conference or Workshop Item (Paper) |
|---|---|
Division/Institute: |
08 Faculty of Science > Institute of Computer Science (INF) > Communication and Distributed Systems (CDS) 08 Faculty of Science > Institute of Computer Science (INF) |
UniBE Contributor: |
Alyafawi, Islam Fayez Abd |
ISBN: |
978-1-4673-0905-9 |
Publisher: |
IEEE |
Language: |
English |
Submitter: |
Dimitrios Xenakis |
Date Deposited: |
04 Oct 2013 14:42 |
Last Modified: |
05 Dec 2022 14:13 |
Publisher DOI: |
10.1109/PerComW.2012.6197572 |
URI: |
https://boris.unibe.ch/id/eprint/17250 (FactScience: 224997) |
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