Hier finden Sie wissenschaftliche Publikationen aus den Fraunhofer-Instituten.

Spectrum utilization assessment of Wi-Fi network using qualcomm/atheros 802.11 wireless chipset

: Adeleke, M.J.; Grebe, A.; Kretschmer, M.; Moedeker, J.


Odumuyiwa, V.:
e-Infrastructure and e-Services for Developing Countries : 9th International Conference, AFRICOMM 2017 : Lagos, Nigeria, December 11-12, 2017, Proceedings
Cham: Springer International Publishing, 2018 (Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 250)
ISBN: 978-3-319-98827-6
ISBN: 978-3-319-98826-9
ISBN: 978-3-319-98828-3
International Conference on e-Infrastructure and e-Services for Developing Countries (AFRICOMM) <9, 2017, Lagos>
Fraunhofer FIT ()

Wireless spectrum is a scarce resource and with the market boom of wireless technology over the years, unlicensed spectrum has become over-crowded with different wireless standards. In this paper, we proposed and demonstrated a proof of concept solution using FFT spectral scan with two methodologies: MaxHold-RMS approach and percentage ratio count approach. Both approaches could be used to detect a free/best channel from different scanned channel on the spectrum. The subsequent contributions were made to knowledge: an FFT based visual spectrum analyzer tool, an algorithm to classify different frequency channel on a spectrum, an algorithm which calculate frequency channel scores using weighted sum model, and channel ranking model. After different experimental evaluations coupled with the FFT spectral sampling timing, operation, a one(1) second scan duration is enough to detect signal transmission from a permanent device on the frequency spectrum since management and control frame signals are always transmitted periodically, while there is little chance for detecting a sporadic signal transmission from the non-permanent user since the FFT spectral scan is performed in passive mode. But to guarantee detection of such sporadic signals then scanning longer at different time segment of the day on the spectrum will increase the probability of detecting such some sporadic signals. Also, the FFT spectral scan capability has shown a high degree of probability for detecting non-WiFi signal on the shared spectrum using Qualcomm/Atheros chipset.