# Experimental Study of LoRa Transmission over Seawater
## 4 Experimental Results and Analysis
### LOS Scenario
#### 4.1.1 ISM 868 MHz
Examining Figure 8 and taking into account the tolerances of components, this can be explained by saturated SNR measurement chain, which shows the \"saw-tooth\" oscillating behavior for the input signal levels higher than \(-100\) dBm. Figure 12 represents RSS and SNR histograms, based on the distribution of 1-min window moving average values, and differences between moving average values and current values for the same LoRa parameters. The distribution of the RSS amplitudes is obviously not Ricean, but it is expected since multipath propagation effect was present during only one interval of the experiment. Again, this has to be interpreted cautiously due to already mentioned reasons. The distribution for the difference between the 1-min window moving average values and current values can be approximated with Gaussian only in the SNR case, while for RSS bimodal distribution is observed. This can be explained  
Figure 11: RSS, SNR, and PRR for ODT, Libelium, and Uputronics at 868 MHz in LOS channel conditions for \(BW=125\) kHz, \(SF=10\), and \(CR=4/6\). with the presence of relatively pronounced multipath effects during one period of the experiment; however, further measurements are needed that would relate RSS bimodal distribution with multipath effects present in a limited interval within the experiment. In Figure 13, results for \(BW=125\,\mathrm{kHz}\), \(\mathrm{SF}=12\), and \(\mathrm{CR}=4/6\) are given. The small fluctuations of RSS for all three transceivers, approximately \(2\,\mathrm{dB}\) peak-to-peak, indicate that there was an unobtrusive multipath propagation, whose effects were not detrimental for PRR. On the other hand, sporadic packet loss that Libelium experienced is a consequence of short burst radio-interference, as can be seen on the plots. This claim is also additionally supported by the fact that moving averages of the RSS and SNR are significantly higher than the link margin during the whole measurement interval. We also observe that SNR follows RSS fluctuation trend for all three transceivers for most of the time, except for ODT: around the 250 and 325 min of the experiment we again notice that SNR decreases when RSS increases; a closer look reveals that RSS again reached \(-100\,\mathrm{dBm}\), replicating the same effects as in the previous experiment. Finally, by comparing the SNRs, it can be again noticed that ODT has the lowest noise floor and, consequently, the highest sensitivity. Figure 12: RSS and SNR histograms for ODT, Uputronics and Libelium: \(f=868\,\mathrm{MHz}\), \(BW=125\,\mathrm{kHz}\), \(SF=10\), \(CR=4/6\), LOS. The histograms for the same experiment scenario, presented in Figure 14 confirms the reasoning applied in the previous experiments. Due to small-scale effects of multipath propagation, the distribution of the differences between RSS moving average values and current values is not bimodal; however, this has to be additionally confirmed with further experiments to be able to be generalized. Figure 14: RSS and SNR histograms for ODT, Uputronics and Libelium: \(f=868\,\mathrm{MHz}\), \(BW=125\,\mathrm{kHz}\), \(SF=12\), \(CR=4/6\), LOS. Figure 13: RSS, SNR, and PRR for ODT, Libelium, and Uputronics at \(868\,\mathrm{MHz}\) in LOS channel conditions for \(BW=125\,\mathrm{kHz}\), \(SF=12\), and \(CR=4/6\).