## 3 Results and Discussion
### Analytical and Deep Learning Results  
In Figure 5, the optimum required interference power (\(P_{I}\)) versus required system QoS is illustrated and compared with different \(\mathit{SINR}_{th}\). Assuming that the transmission distance between V and X is 50 m and the vehicle transmission power is 23 dBm (\(P_{V}\)). As it can be seen, the results obtained from the numerical and deep learning algorithm are identical for different \(\mathit{SINR}_{th}\) and different required QoS. Additionally, it can be mentioned that increasing \(\mathit{SINR}_{th}\) decreases the optimum required interference power to fulfill the required QoS. For example, when \(\mathit{SINR}_{th}\) is 0 dB and the required QoS is 0.99 the optimum required interference power (\(P_{I}\)) must be in the range of 17 dBm, while when \(\mathit{SINR}_{th}\) increases, for example, 10 dB the interference power should be in the range of 7 dBm to satisfy the required QoS, which is 0.99. It is worth mentioning that reaching a QoS of 0.975 with the highest \(\mathit{SINR}_{th}\) (20 dB), as it is considered one of the highest network performance requirements, is required to control and reduce the interference power (\(P_{I}\)) to the value of approximately 1.55 dBm. Figure 4: Training and validation mean absolute error generated during training the proposed model using two-thirds of the dataset. The required interference power (\(P_{I}\)) needed to satisfy different required QoS versus transmission distances between V2X is examined in Figure 6. It is assumed that the required \(SINR_{th}\) is 10 dB and the vehicle transmission power (\(P_{V}\)) is 23 dBm. Figure 6 depicts that increasing the QoS decreases the required interference power (\(P_{I}\)) for both numerical and deep learning methods, which assures the result obtained in Figure 5. Additionally, it can be mentioned that the required interference power (\(P_{I}\)) for each required QoS remains approximately the same when the transmission distance between V2X increases. This is because the system QoS is affected by different parameters, such as path loss and channel noise, which already exist during data transmission. Therefore, the required interference power (\(P_{I}\)) should remain constant while increasing the transmission distance between V2X to overcome the side effect of other network conditions. It can be concluded from this figure that the required QoS is an important parameter that indicates how the system should deal with the interference power. The overall achievable data rate for the proposed model is shown in Figure 7, with the same system parameters assumed in Figure 6. The proposed approach shows that for both numerical and deep learning methods, the system can always achieve the same achievable data rate with different required QoS. This is due to the interference power control provided using the proposed approach. It can be also mentioned that increasing the transmission distance decreases the overall achievable data rate; this is due to the other channel parameters that affect the system performance, such as path loss and channel noise. The required interference power (\(P_{I}\)) is evaluated once again in Figure 8 while monitoring the effect of changing the vehicle transmission power (\(P_{V}\)). Assuming that the required \(SINR_{th}\) is 10 dB and the required QoS is 0.99. Figure 8 observes the interference power (\(P_{I}\)) needed to fulfill the required system performance. It can be shown that increasing \(P_{V}\) increases \(P_{I}\) and leads to overcoming the interference power and enhancing system performance for numerical and deep learning methods. Additionally, the required \(P_{I}\) remains constant when increasing the transmission distance between V2X, due to other factors that can affect the system performance, which requires having the same \(P_{I}\) with transmission distance between V2X. Furthermore, it is worth mentioning from this figure that vehicle transmission power has an important role in decreasing the interference occurring at any transmission link.