## 4 Experiment and Analysis
### Simulation Results  
Figure 13 plots the coverage distance \(d_{6}\) of gNodeB under different effective height \(h\) and the horizontal distance \(d_{3}\). The maximum \(d_{6}\) on rail of HSRs is not more than 1.2 km. This picture shows that as the \(d_{3}\) increases, the range of \(d_{6}\) is extended in the range of 1 km. When the \(h\) increases, the distance \(d_{6}\) has hardly improved.  
The length of the handover zone is one of the important factors to determine the spacing of gNodeBs. The study of path loss in different scenarios of HSRs is helpful for the rational planning of the handover zone. The power attenuation of wireless signals received under different path-loss models (COST 231 and TS 36.942) and different regional types (suburban and urban areas) are different, as shown in Figure 14. The path loss of suburban terrain and free space in TS 36.942 is relatively low, and the changing trend of path loss in the distance between UE and gNodeB is basically the same in the other four cases.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Parameters** & **Value** \\ \hline Frequency & 2.6 GHz \\ Bandwidth & 100 MHz \\ \(n\)Tx/\(n\)Rx & 4/4 \\ TM & 3 \\ \(d_{1}\) & 1.5 km \\ \(h\) & 25 m \\ Antenna mechanical dip angle & 3\({}^{\circ}\) \\ Antenna electronic dip angle & 6\({}^{\circ}\) \\ Antenna gain & 21.5 dB \\ Minimum coupling loss & 58 dB \\ \(V_{\text{thr}}\) & 120 km/h \\ \(D_{\text{thr}}\) & 0.9 km \\ \(\alpha\) & 0.75 \\ Moving speed of HST & 150/250/350/450 km/h \\ \hline \hline \end{tabular}
\end{table}
Table 2: Configuration of parameters.  
Figure 13: Relationship between \(h\), \(d_{3}\) and \(d_{6}\).  
Figure 15 displays the delays of the handover with two algorithms at different speeds of HST. Since the process of the fast handover algorithm is optimized, the delay of the control plane is greatly shortened. This is basically consistent with the results of the theoretical analysis. When the speed increases gradually, the delay of the fast handover algorithm is steadily improved due to the optimized measurement mechanism and execution process. Compared with the A3 handover algorithm at speeds 150 km/h, 250 km/h, 350 km/h and 450 km/h, the delays of the fast handover algorithm are reduced by 1.39%, 1.94%, 2.26%, and 2.54%, respectively. The advantage of the fast handover algorithm makes full use of the characteristics of HSRs, such as known train running line and recognizable handover chain, thus reducing the redundant overhead of time.  
Figure 14: Path losses under different scenarios and different models.  
Figure 15: Comparison of the delays of the handover between the fast handover algorithm and the A3 handover algorithm. Marks represent the bin averages of different handover delay intervals, and bars correspond to the standard deviation in each bin.  
The success rate of the handover, which directly affects the key indexes such as drop rate and throughput, is one of the important indexes to measure wireless communications. The expression of the success rate of the handover is  
\[P_{\text{han}}\ =\ 1-\frac{N_{\text{fai}}}{N_{\text{att}}} \tag{17}\]  
where \(N_{\text{fai}}\) is the number of failed handovers, and \(N_{\text{att}}\) is the number of attempted handovers. When the times of the handover exceed 450, the success rates of the handover of both algorithms tend to be stable as shown in Figure 16. Taking 1000 times of the handover as an example, the success rate of the handover is increased by 0.42% on average at the four speeds of HST. Based on the above analysis, the inter-macro cell of handover and the conventional scheme of handover reach the same success probability of handover [17]. The proposed fast handover algorithm has a more stable and superior success rate of the handover. The fast handover algorithm and inter-macro-cell handover [32] reach the same effect: they not only reduce the delay of the handover but also improve the success rate of the handover.