Comparative analysis of RSSI, SNR and Noise level parameters applicability for WLAN positioning purposes

In this paper, the extensive experimental analysis of RSSI, SNR and Noise level parameters usefulness for WLAN positioning purposes was conducted. Four positioning models, based on artificial neural networks, with RSSI, SNR, Noise level and both RSSI and SNR as network's inputs, were created, trained and verified. The obtained results have shown that, contrary to the common knowledge, SNR parameter is equally suitable for WLAN positioning purposes as RSSI parameter. In addition, the obtained results pointed out that the space distribution of the noise level parameter contains less location dependant information than RSSI or SNR.

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