# A Survey of Handover Management in Mobile HetNets: Current Challenges and Future Directions
## 4 Handover Decision Techniques
### FLC-Based HO Decision Approaches  
Fuzzy logic is a technique that attempts to find accurate solutions for problems with imprecise data. In simple words, it allows situations, problems, or actions to be described and processed in linguistic terms such as \"low\", \"medium\" and \"high\" instead of values like \"30 kmph\", \"70 kmph\" and \"120 kmph\" [155]. It has been employed in a variety of engineering applications. FL approaches can be used in mobile communications to determine when and which cell to handover. These decisions can be based on multiple criteria and attributes as shown in Figure 8 for an enhanced decision-making procedure. In this subsection, we highlighted the recent literature that employed the FL-based approaches for handovers in the HetNets environment. Due to HetNets and dense cell deployment in 4G LTE and 5G networks, the probability of HOPP, HOF and RLF on high-speed UE has increased tremendously. That is why managing and optimizing the HCP values is required by adjusting the conflicts between MRO and LBO. In this article [84], the authors proposed a coordinated self-optimization technique based on fuzzy logic to perform seamless handovers in HetNets. To manage the HO parameters along with adjustment of MRO and LBO conflict, authors used Cell Load instead of LBO and Weighted FLC for MRO to get optimized values of HCP according to the input parameters. Simulation results were compared based on HOPP, RLF and HOL. Previously the same author in [77] employed FL by proposing a weighted fuzzy self-optimization approach to optimize HCP parameters in HetNets. They optimize the HOM and TTT by taking SINR, UE speed, and BS traffic load into account as input parameters. The weighted fuzzy algorithm automatically optimizes the HCP values according to the  
\begin{table}
\begin{tabular}{p{42.7 pt} p{42.7 pt} p{42.7 pt} p{42.7 pt} p{42.7 pt} p{42.7 pt}} \hline \hline
**Ref. No** & \begin{tabular}{c} **Criteria** \\ **Parameter** \\ **Selection** \\ \end{tabular}  & **HCPs** & **KPI’s** & **Simulator** & **Achievement** & **Drawbacks** \\ \hline
2019 [92] & RSRP & \begin{tabular}{c} HOM, \\ TTT \\ \end{tabular}  & \begin{tabular}{c} HOPP, \\ HOP \\ \end{tabular}  & \ \begin{tabular}{c} RLF, \\ HOP \\ \end{tabular}  & MATLAB & \begin{tabular}{c} Velocity aware technique HOPP, RLF and IT by 78.31\%, 49.86\% and 44.94\% respectively as compared to static HCP approach \\ \end{tabular}  & According to the Handover types, TTT and HOM values are adjusted, but these step based jumping adjustments in HCP shows fixed behavior \\ \hline
2019 [37] & RSRP, UE Velocity & \begin{tabular}{c} HOM, \\ TTT \\ \end{tabular}  & \begin{tabular}{c} HOPP, \\ HOP, \\ HOD, HIT \\ \end{tabular}  & \ \begin{tabular}{c} RLF, \\ HOP, \\ HOD, HIT \\ \end{tabular}  &
\begin{tabular}{c} Proposed Auto-Turning Algorithm re  
input parameters. They compared the simulation results on the basis of RLF, HOPP and HOF. In [102], authors proposed a fuzzy logic-based vertical handover decision-making scheme for HetNets using only throughput and end-to-end delay as input parameters. Simulation results compared on the basis of throughput, end-to-end delays, jitter and handover decision time. The authors extended their previous work [79] in this [87] article by employing fuzzy logic to optimize only the HOM value by using RSRP, RSRQ and UE velocity as inputs to fuzzification system. They achieved the dynamic HOM values by enhancing the fuzzy rules from the previous work according to the quality and velocity of the UE. The simulation results were compared to numerous approaches based on HOF, HOPP, number of HOs, and average connection time. A three-stage fuzzy logic handover approach was proposed in [109] for the D2D scenario. They used RSRP, PLR and throughput as input criteria to the fuzzification system and developed a minimum quality function to estimate the handover necessity; the purpose was to reduce the unwanted handovers. In the second stage, they designed a fuzzy logic-based target cell selection scheme to process the UEs requiring handovers.