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D. Neunteufel, A. Fuchs, H. Arthaber:
"ToF-based Indoor Positioning for Low-power IoT Nodes";
Vortrag: Asilomar Conference on Signals, Systems, and Computers, California, USA; 01.11.2020 - 04.11.2020; in: "54th Annual Asilomar Conference on Signals, Systems, and Computers", (2020), 5 S.

In this work, we address the challenge of using power and complexity-limited internet of things (IoT) nodes for time of fligh (ToF)-based indoor localization. This requires a high signaling bandwidth, and thus the narrowband radiosmany low-power, low-cost, commercial off-the-shelf (COTS)transceiver chips can not be used. However, as these kind of nodes are deployed in vast numbers, it is worth considering unorthodox approaches to facilitate wideband signal generation without changes to the hardware. We make use of an unsupported mode of operation of one typical transceiver chip to generate frequency-stepped chirp waveform with a bandwidth of up to 80 MHz in the 2.4 GHz industrial, scientific and medical (ISM) band.
This paper evaluates a pulse-compression technique for such chirped signals, which accounts for unknown properties of non-ideal transceivers. This edge computing approach allows for an immediate rate reduction of the received data and the application of efficent localization algorithms in the cloud. The performance of the phase difference estimation as the crucial step of the pulse-compression is evaluated using a Monte Carlo simulation of the introduced channel and processing chain. We compare it to the theoretical bound for an ideal waveform.

internet of things, indoor localization, radio frequency, time of flight, software-define radio, edge computing