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Parameter estimation techniques for indoor localisation via WiFi

Ahmad Bazzi 1 
Abstract : In an indoor environment, the problem of extracting the Angle-of-Arrival of the Line-of-Sight component between a transmitter and Wi-Fi receiver using a SIMO link is the main concern of this thesis. One main challenge in doing so is due to the rich multipath channel that indoor environments enjoy. This is so because multipath results from the fact that the propagation channel consists of several obstacles and reflectors. Thus, the received signal arrives as an unpredictable set of reflections and/or direct waves each with its own degree of attenuation and delay. Other challenges are limitation of resources, such as number of antennas, available bandwidth, and Signal-to-Noise-Ratio; not to mention the Wi-Fi ”imperfections”, such as gain/phase mismatches between antennas and synchronisation issues between transmitter and receiver. In this thesis, our main focus is implementing a real-time system that could measure the angle between a transmitter and receiver in the presence of all challenges. In particular, we have taken into account all factors that perturb the Joint Angle and Delay estimation problem and formulated a system model accordingly. These factors are: Sampling Frequency offset (SFO), Carrier Frequency Offset (CFO), Phase and Delay offsets at each antenna. To compensate for the effect of these critical factors, we propose an offline calibration method to compensate for all their effects. This thesis will also include other theoretical methods that have to deal with Angle-of-Arrival Estimation problem from compressed sensing and signal processing point of views.
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Submitted on : Wednesday, March 21, 2018 - 7:16:07 PM
Last modification on : Thursday, November 4, 2021 - 3:11:38 AM
Long-term archiving on: : Thursday, September 13, 2018 - 8:21:19 AM


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  • HAL Id : tel-01740339, version 1



Ahmad Bazzi. Parameter estimation techniques for indoor localisation via WiFi. Signal and Image processing. Télécom ParisTech, 2017. English. ⟨NNT : 2017ENST0051⟩. ⟨tel-01740339⟩



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