# Path Difference Optimization of 5G Millimeter Wave Communication Networks in Malaysia
## 6 Simulation Results
In this paper, we estimate both the LOS and NLOS probabilities in the outdoor urban and highway scenarios. The outdoor LOS and NLOS probabilities for the urban and highway scenarios are shown in Figures 5-8, respectively. The LOS and NLOS probabilities in the highway and urban scenarios are affected by the path difference and vehicle density parameters. From Figure 5, it can be noticed that the LOS probability decreases gradually as the path difference (0-500 m) increases, which is because in the urban region the signal propagation path is effected by obstructions such as high-rise buildings, trees, advertising signs, etc. These obstructions cause multi-path fading, which reduces the signal's energy. In addition, the LOS probability is influenced by the vehicle density, decreasing as the vehicle density increases. Vehicles traveling along the propagating mmWave signal path increase signal fading and absorption, thereby reducing the received signal strength. Therefore, increased path differences and vehicle density decrease the LOS probability in the outdoor urban region. Figure 6 shows the LOS probability variation with a path difference of (0-500 m) in the highway scenario for various vehicle densities. From Figure 6, it can be noticed that the LOS probability decreases with the path difference and vehicle density. However, the LOS probability of the highway scenario is higher than that of the urban scenario, as the  
Figure 5: LOS probability for the urban scenario for a path difference of 0–500 m.  
Figure 6: LOS probability for the highway scenario for a path difference of 0–500 m.  
LOS path in the urban scenario is obstructed by a greater number of obstructions such as high-rise buildings, lamp posts, advertisement boards, etc., compared to the highway scenario. On highways, the signal is able to propagate in free space, and the optimal distance is higher in the highway scenario compared to the urban scenario. Figures 7 and 8 show the NLOS probabilities for the urban and highway scenarios, respectively. When the LOS path is obstructed by trees, buildings, or vehicles, it is termed the NLOS path. In 3 GPP outdoor models [44], these distinctions are not made. For a short path difference, the path between the transmitter and receiver is assumed to be free of obstructions. As a result, in both cases the probability increases with the path difference and vehicle density. It can be observed that the NLOS probability is high in the urban scenario compared to the highway scenario, which is exactly opposite to the LOS probability seen in Figures 5 and 6. The observed path loss is substantially lower, pointing to a wave guide effect brought on by reflections from static obstacles in street canyons, which are more likely to occur. Figure 10 shows the NLOS path loss of the urban and highway scenarios with and without rainfall. According to 3 GPP models, there is no variation in the path loss for the urban and highway scenarios [45]. From this figure, it can be noticed that the path loss is high when there is heavy rainfall compared to a clear sky. Therefore, from all these results it is the case that the path loss depends on the path difference, rainfall intensity, and operating frequency. The path loss and path attenuation increase as the path difference, operating frequency, and rainfall intensity increase, as observed in Figures 1, 2, 9 and 10. Along with these, the path loss performance depends on the antenna height, tilt angle, and antenna location or position [46,47]. Equation (20) is used to calculate the link margin with rainfall attenuation. The link margin is estimated at \(P_{t}=27\) dBm, \(T_{s}=30.62\) dB, and \(K=1.38*10\)-23 dB for variable antenna gains and free space path loss with mmWave frequencies ranging from 1 GHz to 100 GHz and path differences ranging from 100 m to 1 km.