# Neural Network SNR Prediction for Improved Spectral Efficiency in Land Mobile Satellite Networks
## 4 Results and Discussion
### Single Channel Spectral Efficiency
This simply shows that the errors that NN makes can be such that the SNR prediction itself is better, but the overestimating of values that sometimes occur can have a negative impact on reaching certain goals, such as low rates of transmission error. In terms of obtainable improvement for light shadowing, for a frequency range of 40 MHz, if the best relative improvement scenario is considered for NN2 (\(f_{Dm}\) = 75 Hz, SNR = 9 dB), the contribution of NN2 would be (1.12 - 0.92) b/s/Hz \(\times\) 40 MHz = 8 Mb/s. Observing average shadowing, similar patterns can be observed for light shadowing, with some changes. Firstly, for average shadowing, for an expected SNR of 3 dB, the transmission error rate was always higher than 0.01. This is because more frequent or heavier shadowing increases the intervals in which no communication can occur, thus raising the unavoidable error, which exceeds 0.01 in these scenarios. It can also be seen, in comparison to the low shadowing conditions, that for higher \(f_{Dm}\) values, the achieved spectral efficiencies are overall quite lower, while for the lower \(f_{Dm}\) values, this is not as prominent. This is to be expected as the combination of quicker changes in SNR in combination with more frequent shadowing makes predictions significantly more difficult, whereas if more shadowing but for slower changing SNR channels (lower \(f_{Dm}\)), the SNR pattern during shadowing can be more easily predicted and therefore not hinder the performance as severely. One more important observation is that although the absolute values are overall lower for higher \(f_{Dm}\) when compared to the light shadowing, the relative improvement between OI and NN2 is more pronounced. This would indicate that for less favorable scenarios, such as average shadowing and a high \(f_{Dm}\), although the absolute spectral efficiency cannot be high, introducing more complex algorithms for SNR prediction could provide a significant benefit. Another occurrence that has happened for light shadowing was that in certain scenarios, NN has a transmission error rate higher than 0.01 while OI and NN2 do not. This has now happened for \(f_{Dm}\) of 50 Hz and an expected SNR of 6 dB for the same reason described in the light shadowing scenario. Once again, in the results obtained for heavy shadowing, it can be seen that the expected SNR of 6 dB does not allow for communication under any \(f_{Dm}\) conditions. For the average shadowing, in terms of obtainable absolute improvement (for a frequency range of 40 MHz), the best relative improvement scenario for NN2 (\(f_{Dm}\) = 100 Hz, SNR = 12 dB), the contribution of NN2 would be (0.54 - 0.32) b/s/Hz \(\times\) 40 MHz = 8.8 Mb/s. The analysis of the results obtained for heavy shadowing is quite similar to the one for previous scenarios. The transmission error rate was higher than 0.01 (due to outage probability) for almost all \(f_{Dm}\)s and the expected SNR up to 9, with the only exception being the SNR of 9 dB and \(f_{Dm}\)s of 5 Hz. This shows that, as in the examples above, sometimes channel SNR values can play out in such a way that they allow for communication to be established in a way that is not possible for similar scenarios. One more important observation that stands for all shadowing conditions but can best be seen for heavy shadowing is that even in the scenarios where the transmission error rate is higher than 0.01, the improvements of spectral efficiency exist between OI and NN2 and the absolute value of spectral efficiency rises with the rise of the expected SNR. This is extremely important because even if a desired error rate is unattainable, this approach will still provide an improvement in spectral efficiency, which is crucial when considering multiple channels with different characteristics and the usability of the provided method. The relative improvement provided in certain scenarios for heavy shadowing is the highest among the observed scenarios and exceeds 100% in some cases.