# A Survey of Handover Management in Mobile HetNets: Current Challenges and Future Directions
## 3 Background
### Self Optimization Network in HetNets  
The extensive use of SON in numerous domains makes it difficult to define precisely. However, somehow we can demonstrate it as an efficient way to manage the dynamic requirements in a distributed environment. Similarly, it can be described as a method or technique that allows a system to modify its organization without explicit command during execution [48].  
In 2008, Self-configuration and Self-optimization networks were introduced as a part of LTE networks [49] and been standardized in 2009 starting from release 9 [50]. The aim of this deployment for LTE was to achieve the expected network performance indicators named KPIs. Such as capacity, coverage, QoS, user satisfaction, CAPEX/OPEX, etc. Later on, this SON concept was extensively adopted in telecom sectors for performance optimization techniques and worked as a fundamental part for 4G mobile networks, as well as 5G networks [51; 52; 53; 54; 55; 56]. Three categories are designated for SONs: Self-configuration, Self-optimization, and Self-healing. Self-configuration autonomously adjusts the parameters according to the condition without human intervention. Whereas, Self-optimization is the procedure that automatically optimizes the parameters after the configuration proposed by the network or system. Lastly, Self-healing works to recede errors and faults from the network by adopting suitable actions suggested after optimization [24]. Several autonomous functions for self-optimization have been introduced for 4G and 5G systems. The functions defined under this are mostly related to the optimization of [24; 53; 54]:  
* Coverage and Capacity
* Handovers
* Interference  
This article focuses on HO-based matters, so here we will discuss the SON parameters that only relate to HO and mobility management. LBO and MRO work as HCP controlling functions that automatically optimize the values for HOM and TTT. As HOs have a time constraint set by the 3 GPP, these SONs have to provide optimized results in a real-time scenario to reduce the latency as well as to maintain connectivity and quality according to the user requirements. Due to certain requirements and conditions, MRO and LBO parameter settings may conflict or be compromised. Both functions seek to optimize the HCPs in order to increase HO performance. For example, the MRO function adjusts HCPs based on user mobility, whereas the LBO function adjusts HCP values to balance load among cells, resulting in a conflict. Many authors have tried to resolve the issue [38; 57; 58; 59; 60], but it still requires attention to produce an optimal value for HCPs.  
\begin{table}
\begin{tabular}{c c c c c c} \hline
**Serial. No** & **UE Speed** & **HOM** & **TTT** & **HOF** & **HOPP** \\ \hline
1 & Increase & Low & Low & Lower & Lower \\ \hline
2 & Increase & Low & High & Higher & Lower \\ \hline
3 & Increase & High & High & Higher & Lower \\ \hline
4 & Increase & High & Low & Higher & Lower \\ \hline
5 & Decrease & Low & Low & Higher & Higher \\ \hline
6 & Decrease & Low & High & Higher & Lower \\ \hline
7 & Decrease & High & Low & Lower & Higher \\ \hline
8 & Decrease & High & High & Lower & Lower \\ \hline \end{tabular}
\end{table}
Table 2: Summary of HCP parameters for HOF and HOPP.