# Neural Network SNR Prediction for Improved Spectral Efficiency in Land Mobile Satellite Networks
## 4 Results and Discussion
### Single Channel Spectral Efficiency  
Considering the achieved results, it is clear that the neural networks can provide clear improvement in terms of SNR prediction when compared to the baseline OI approach, and the next step represents the evaluation of spectral efficiencies for all observed channels. The initial step is to analyze the outage probabilities if perfect SNR predictions would have been performed for the test channels, presented in Table 5. These outage probabilities present the unavoidable error on the test set and are relevant for the interpretation of further results. The results show that for the set threshold of 0.01 for single channel evaluation, outage probability is too high in some scenarios, making the set threshold unobtainable. These outage probabilities, however, should not impair the improvements in spectral efficiency that the neural networks should offer. The outage probabilities are more prominent for higher levels of shadowing, which is expected as 1 percent of the test set corresponds to 250 samples, and more frequent, heavier shadowing can easily make more than 250 samples have values lower than the minimum operational threshold. Table 6 shows the results in terms of spectral efficiency and achieved error transmission rate for all considered conditions and algorithms. Figures 5-7 show the relationship between the SNR and the achieved spectral efficiency for light, average and heavy shadowing, respectively, while Figures 8-10 show the results visually in terms of improvement percentage compared to the OI spectral efficiency for light, average and heavy shadowing, respectively. The results in Table 6 show the wide range of performances that can be achieved for various scenarios and again point out that different channel characteristics can quite heavily influence the performance of the algorithms. Expectedly, as opposed to the MSE results, the expected SNR plays a significant role in achieving higher spectral efficiency. More specifically, the higher the expected SNR, the higher the achieved spectral efficiency. Figure 5: The achieved spectral efficiency on the test set for various scenarios under light shadowing conditions using a single channel. Figure 6: The achieved spectral efficiency on the test set for various scenarios under average shadowing conditions using a single channel. Figure 7: The achieved spectral efficiency on the test set for various scenarios under heavy shadowing conditions using a single channel. This stands regardless of the implemented algorithm or \(f_{Dm}\) value. It is also important to note that there are many scenarios for which the transmission error rate is higher than 0.01, essentially making reliable communication impossible, regardless of the spectral efficiency that can be achieved. As can be seen in Table 5, all of the scenarios for which the desired error rate of 0.01 is not achieved have an unavoidable transmission error higher than 0.01. The implemented approach for margin determination does not make achieving an error of less than 0.01 on the test set certain, as the margin is determined on the training set and only then applied on the test set. However, the results indicate that this approach works quite well, as all the scenarios in which the error is larger than 0.01 correspond to the ones where the unavoidable outage probability is above 0.01. Figure 8: The achieved spectral efficiency improvement in % compared to the OI, on the test set for various scenarios under light shadowing conditions using a single channel. Scenarios where the transmission error is <0.01 are shown in blue, and scenarios where the transmission error is >0.01 are shown in red. Figure 9: The achieved spectral efficiency improvement in % compared to the OI, on the test set for various scenarios under average shadowing conditions using a single channel. Scenarios where the transmission error is <0.01 are shown in blue, and scenarios where the transmission error is >0.01 are shown in red.