## 4 Numerical Results  
This section provides numerical and simulation results in terms of the outage probability over Rayleigh fading channels. We run \(10^{6}\) iterations for Monte Carlo simulation results. We try to simulate with a high number of trials to provide the simulation results more precisely and and hence analytical results are closer to the theoretical results. Our results depend on the iterations of a Monte Carlo simulation where the sample mean is computed, followed by the population mean, and then calculate a 95% confidence interval for each observation. In particular, we set power allocation factors as \(a_{1}=0.8\), \(a_{2}=0.2\), the channel gains \(\Omega_{SR}=5\), \(\Omega_{SP}=\Omega_{RP}=0.1\), \(\Omega_{RD_{1}}=1\), \(\Omega_{RD_{2}}=2\), \(I=20\) dB, \(R_{1}=R_{2}=1\) (bits/s/Hz), \(\eta=0.9\) and \(K=1\) except for specific cases. Figure 2 shows the outage performance related to the ability of detecting \(x_{1},x_{2}\) at \(D_{1},D_{2}\), respectively. It can be seen that, when increasing SNR at the BS, a higher level of power is used to signal processing, then outage improvement is archived, and hence significantly low outage performance at a high SNR regime is achieved. When we set \(I=20\) (dB), the outage performance of two vehicles are better than the case of \(I=10\) (dB). The other observation is that the outage of the second vehicle shows better performance than that of the first vehicle and the performance gap is clearer at high SNR values (SNR is greater than 20 dB). The reason is that \(D_{2}\) eliminates interference from \(D_{1}\) by deploying SIC, so SNR achieved at \(D_{2}\) is higher than at \(D_{1}\). It can be further explained that \(D_{1}\) detects the desired signal without eliminating interference from other vehicles that makes the probability worse. Moreover, the simulation results by using Monte Carlo match very well with the analytical ones. This confirms the correctness of the derived closed-form expressions related to outage behavior of two vehicles. Figure 3 compares the outage performance of two vehicles for different values of the number of RSUs. It can be observed from the same figure that \(D_{2}\) achieves a smaller outage probability compared with that of \(D_{1}\) regardless of any number of RSU. \(K=5\) exhibits as the best performance to indicate a role selecting a better signal among larger numbers of RSU. Figure 3 also shows that, although better  
Figure 2: Outage performance of two vehicles versus SNR at the BS with different \(I\). outage can be obtained by increasing SNR from 0 (dB) to 20 (dB), an increase in SNR at the BS over this point (20 dB) still meets the saturation of outage behavior at a high region of SNR. Interestingly, a larger performance gap among two vehicles can be seen clearly at high SNR. The main reason is that different conditions of signal detection and different power allocation factors are assigned to each signal. Figure 4 illustrates that such outage performance is affected by the amount of harvested energy at RSU. When \(\eta\) is small, it means the amount of harvested energy is reduced. This situation makes the outage performance becomes worse value. However, we only see larger performance gaps among three cases \(\eta=0.3,0.5,0.9\) at a low region of SNR. It is further observed that the outage probability decreases significantly as this energy efficiency \(\eta\) increases as in Figure 5. This figure confirms the higher power of primary users contributing to enhanced performance of secondary networks. Therefore, the advantage of the cognitive radio and energy harvesting schemes benefit V2X to guarantee operation of both networks (secondary and primary networks). Figure 3: Outage performance of two vehicles versus SNR at the BS with different \(K\). Figure 4: Impact of percentage of harvested power at RSU on outage performance. Figure 5: Impact of percentage of harvested power at RSU on outage performance with different cases of \(I,P\).