Energy detection based spectrum sensing for rural area networks
Vartiainen, Johanna; Karvonen, Heikki; Matinmikko-Blue, Marja; Mendes, Luciano; Saarnisaari, Harri; Matos, Alexandre (2020-04-07)
Vartiainen, J., Karvonen, H., Matinmikko-Blue, M., Mendes, L., Saarnisaari, H., & Matos, A. (2020). Energy Detection Based Spectrum Sensing for Rural Area Networks. EAI Endorsed Transactions on Wireless Spectrum, 4(13), 163923. https://doi.org/10.4108/eai.7-4-2020.163923
Copyright © 2020 J. Vartiainen et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.
Remote and rural areas are a challenge to deploy cost-efficient connectivity solutions. 5G technology needs lower frequencies, which calls for spectrum sharing for local networks. Spectrum sensing could complement traditional database approach for spectrum sharing in these areas. This paper studies a windowing based (WIBA) blind spectrum sensing method and compares its performance to a localization algorithm based on double-thresholding (LAD). Both methods are based on energy detection and can be used in any band for detecting rather narrowband signals. Probabilities of detection and false alarm, relative mean square error, number of detected signals and detection distances were evaluated in multipath, multi-signal and rural area channel conditions. The simulation results show tha the WIBA method is suitable for 5G remote areas, due to its good detection performance in low signal-to-noise ratios (SNR) with low complexity. Results also show importance of the detection window selection.
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