# A Non-WSSUS Channel Simulator for V2X Communication Systems
## 6 Simulation Examples
### Results of Changes of the Initial Speed  
First, we evaluated the BER performance for a transmission of \(F=64\) data OFDM symbols in each frame at different relative speeds between the MSs by varying both the initial speed and acceleration components. For this simulation, a propagation environment with isotropic scattering was considered (\(\kappa=0\)), that is a scenario that resembles an urban environment with IOs that uniformly surround \(R_{X}\). The BER performance curves for Scenario I are shown in Figure 8, for both the LS estimator and the STA technique. In the case of the LS estimator, the performance decreased when the initial speeds of the MSs were increased from \(\
u_{T}=\
u_{R}=20\) km/h (relative speed of 40 km/h) to \(\
u_{T}=\
u_{R}=100\) km/h (relative speed of 200 km/h) regardless of the propagation scenario. This condition occurred since the Doppler frequency shifts increases as the relative speed also increases. Therefore, the channel presents more variations, and the LS estimation becomes less accurate.  
In fact, the BER performance of the LS estimator is independent of the channel non-stationarities and MSs acceleration components since the channel estimation is carried out with the two initial training symbols on each frame. Consequently, the time variations in a data frame caused by the non-stationarities and acceleration terms could be negligible for the LS estimator. This result is illustrated in Figure 8, which is consistent with [56] for WSSUS channels and with [57] for non-WSSUS channels with constant speed. Concerning the STA technique, the BER performance was poor compared to the LS estimator. Such performance was almost equal to the case where there is no channel estimation at all since the statistics of the non-WSSUS process change as the data transmission proceeds, and the non-stationarities directly impact the weighted average that was carried out in the frequency domain [57; 58]. In this particular case, the channel effect on the system performance due to the acceleration of the MSs was minimal and masked by its inherent non-stationarities [59].  
In addition to the results presented in Figure 8, Table 5 shows the Eb/No levels that attained 10% and 1% BER for the low mobility (20 km/h and 40 km/h) and high mobility (80 km/h and 100 km/h)  
Figure 8: System performance by considering different initial speeds and acceleration components for Scenario I with a constant frame length of \(F=64\).  
conditions in the three propagation scenarios described above. The legend NA denotes that the BER level was not achieved by using the corresponding estimation scheme. In this table, we can observe that the performance of the LS estimator in low mobility conditions was similar for the three scenarios, reaching 10% BER with comparable Eb/No levels. In such conditions, an Eb/No regime greater than 5.5 dB guarantees a BER lower than 10% for all the scenarios. On the other hand, for high mobility conditions, we observed that Eb/No levels greater than 10 dB were required to attain a 10% BER. As observed in Figure 8, the BER performance of this estimator was greater than 0.1% even at high Eb/No regimes for initial speeds of 100 km/h. Furthermore, the results showed that the performance of the LS estimation in Scenario I was the least affected by the high mobility conditions, reaching BER levels lower than 10% with an Eb/No greater than 16.51 dB when the initial speeds were 100 km/h. For the STA technique, its BER performance always remained greater than 10% in these experiments regardless of the propagation scenario although using a large value of \(\alpha\).