# A Survey of Handover Management in Mobile HetNets: Current Challenges and Future Directions
## 4 Handover Decision Techniques
### Spatial Information Aware HO Decision Approaches
On the basis of available values of input parameters, they calculated the weight values by using the analytical hierarchy process (AHP) to acquire handover utility of all the target cells. For analysis, they developed an analytical model as well as a simulation model and performed the comparison based on the number of ping pongs, number of handovers, HOPP and throughput. \begin{table}
\begin{tabular}{p{28.5 pt} p{28.5 pt} p{28.5 pt} p{28.5 pt} p{28.5 pt} p{28.5 pt} p{28.5 pt}} \hline
**Ref. No Year** & **Criteria of Parameter Selection** & **HCP’s** & **KPI’s** & **Simulator** & **Achievement** & **Drawbacks** \\ \hline \multirow{4}{*}{[121]} & UE speed, UE trajectory, UE Location, ESRP & Weight & Packet Radio, Packet Radio & & Evaluation of movement direction distance (MDD) algorithm in different dense network & For comparison purposes, consideration of HOPP, HOF, RLF, etc. can justify the performance in a much better way \\ \cline{2-6}  & HOPP, Frequent HO, CDR, CBR, PLR & Quality Indicator Weight & HOPP, CDR, Unnecessary HO & MATLAB & A Spatio-Temporal Weight estimation approach that reduced the unnecessary HO, HO and HOF by 35\%, 37\% and 17\% respectively \\ \hline \multirow{4}{*}{[100]} & RSRP, SINR, OP & RSRP, SINR, OP & HOPP, No. of SINR, OP & HOPP, No. of HOs, PP Rate & & MADM based multi-attribute scheme that considered UE location in a cell which is divided into non-overlapping regions, results in an improvement in the overall throughput \\ \cline{2-6}  & Distance, RSRP, UE Speed, UE Location, Cell Location & PDR, PLR, Throughput, No. of HOs & PLR, PLR, Time-Sim & Movement direction distance vertical handover (MDD-VHD) scheme reduced the average number of HOs, PDR, PLR, signaling cost of 48\%, 91\%, 86\% and 99\% respectively in comparison with [171] \\ \cline{2-6}  & RSRP, UE Location, Cell Location, Cell Load & past values for HO & PDR, PLR, Throughput, No. of HOs & PLR, PLR, Time-Sim and signaling cost by 19.5\%, 15.6\%, 42\% and 99\% respectively as compared to [172] \\ \hline \multirow{4}{*}{[119]} & RSRP, UE Speed, UE Location, Cell Location & distance, trajectory angle & No. of HOs & MATLAB & A new handover procedure that was based on two policies, the moving direction prediction and the historical information of UEs and reduced the average number of HOs, PDR, PLR and signaling cost by 19.5\%, 15.6\%, 42\% and 99\% respectively as compared to [172] \\ \cline{2-6}  & RSRP, UE Speed, UE Location, Cell Location & distance, trajectory angle & No. of HOs & MATLAB & Use of Lagrange interpolation to calculate the probability of UE transition to its neighbor cell on the basis of the velocity and the slope of the trajectory that reduced the number of HOs upto 30\% as compared to the LTE HO approach \\ \hline \end{tabular}
\end{table} 
Table 10: Spatial Information based Handover Decision Approaches. In general, humans perform geographically limited periodic movements most of the time, which can be used to extract many useful aspects of movement behaviors. A very basic illustration of the scheme is shown in Figure 11, which shows that by utilizing the periodic and time-oriented movement information, the trajectory of a user can be predicted. Which can enhance the performance of the handover approaches greatly. The authors of [116; 121] proposed a movement direction information history handover (MDIH-HD) method in [117] that utilized the concept of historical UE trajectory information and future location prediction for the handover process in LTE-A networks. The basic purpose of this MDIH-HD approach was to enhance the throughput and reduce the cell searching time, number of handovers, packet loss and delay at high speeds. Along with basic signal measurement parameters, they used UE direction, mobility pattern history and target cell load for this scheme. For an expected path, the UE's historical data was utilized, while the moving direction prediction was employed for the random route.