## 3 Proposed System Architecture
### Proposed System and Algorithm
For instance, in [25], the maximum UE speed is considered to be 72 km/h, which impacts the TTT and HOM ranges considered in the ranges of 0 to 200 ms and 0 to 5 dB, respectively. The proposed algorithm in this work will not be efficient for UE speeds greater than 72 km/h. Therefore, prior knowledge of system performance behavior, considering the effects of all input parameters on TTT and HOM, is required when applying a technique like FLC. A static setting of TTT and HOM may lead to unacceptable increases or decreases in RLF and HOMP occurrences. Thus, it is crucial to mitigate both RLF and HOMP occurrences while ensuring a balanced approach that maintains acceptable thresholds. The TTT and HOM MFs are depicted in Figures 7 and 8, respectively. TTT MFs are defined individually for each speed set (degree), whereas the HOM MF is defined as a general status across all speed scenarios within the system. Figure 7 depicts the TTT range for each speed set, with varying illustrations. Overall, the crisp value falls within the range of 80 to 512 ms. Furthermore, Figure 8 illustrates the HOM crisp values ranging between 0 and 16 dB. ## 4 Performance Evaluation

The performance of the proposed algorithm, called velocity-aware fuzzy logic-based HO optimization algorithm (VAFL), was assessed through the use of KPIs, including HOR, HOF, HOPP, and RLF. It has been compared with a conventional A3 event, an FLC-based HO scheme called FLDHDT that dynamically adjusts the values of both HOM and TTT [25], and another competitive method called the individualistic dynamic handover parameter optimization algorithm based on an automatic weight function (IDHPO-AWF) [15]. The comparison methods are labeled as A3, FLD, and AWF in the results. The simulation parameters are listed in Table 2, with values carefully selected based on established standards, reputable literature, and findings from esteemed published papers [33; 34; 35; 36]. ### Handover Rate (HOR)

HOR is used to describe the number of HOs that can occur when a user moves within the network. This metric is also known as the HO probability. Figure 9 illustrates the average HOR versus different aspects: (a) speed, (b) overall the system, and (c) simulation time. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Parameters** & **LTE-A** & **5G** \\ \hline Carrier Frequency (f) & 2.6 GHz & 28 GHz \\ System Bandwidth (B) & 20 MHz & 500 MHz \\ Transmit Power (Tx) & 43 dBm & 30 dBm \\ Cell Radius (R) & 1000 m & 100 m \\ Antenna Height (H) & 25 m & 15 m \\ Number of Cells & 21 & 280 \\ Shadowing (\(\sigma\)) & 8 dB & 10 dB \\ Path Loss Model & \(\mathrm{PL}=40\times(1-4\times 10^{-3}H)\log_{10}(d)-18\log_{10}(H)+21\log_{10}(f)+80 (dB)\) \\ T310 & & 1 s \\ Number of UEs for Evaluation & & 20 \\ User Speeds (v) & [5; 20; 50; 80; 120; 180; 220] km/h \\ Reference Sensitivity (Q\({}_{\mathrm{Rx}}\)) & \(-101.5\) dBm \\ Noise Power Density (N\({}_{0}\)) & \(-174\) dBm/Hz \\ Fast Fading Model & Rayleigh fading \\ UE Measurement Periodicity (MP) & & 40 ms \\ Simulation Period & & 1000 cycles \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Simulation parameters for LTE-A and 5G. Figure 8: HOM MF for all speed scenarios. As shown in Figure 9a, as the UE speeds increase, the HOR also increases. This is mainly due to the UEs moving between multiple cells. Figure 9b shows the average HOR versus the overall system for the proposed method and all the comparing methods. In Figure 9c, the average HOR for all UEs is depicted over simulation time. The initial peak in this graph is due to an increase in HO requests during the initial phases of network operation. During this period, UEs are switching to cells that provide better cell load and signal quality conditions. Our proposed method has better performance than other methods under consideration, where it outperforms A3 by approximately 96.47%, surpasses FLD [25] by 96.20%, and exceeds AWF [15] by 96.26%.