# Multi-Tier Cellular Handover with Multi-Access Edge Computing and Deep Learning
## 3 Related Works
### Summary  
Table 3 summarizes the related works. Where works are found to share similar pros and cons, the discussion of their benefits and drawbacks are merged.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Approach** & **Ref.** & **Solution Summary** & **Benefits and Drawbacks** \\ \hline \multirow{8}{*}{Multi-connectivity} & \multirow{8}{*}{[15]} & \multirow{8}{*}{*} & Proposes to always connect & \multirow{8}{*}{} \\  & & UE to two 5G mm-wave access points and one LTE BS to & & \\  & & reduce HO latency and signaling overhead & & \\ \cline{1-1} \cline{3-4}  & & & & \\ \cline{1-1} \cline{3-4}  & & & & \\ \cline{1-1} \cline{3-4}  & & & & \\ \cline{1-1} \cline{3-4}  & & & & \\ \cline{1-1} \cline{3-4}  & & & & \\ \cline{1-1} \cline{3-4}  & & & & \\ \cline{1-1} \cline{3-4}  & & & & \\ \cline{1-1} \cline{3-4}  & & & & \\ \cline{1-1} \cline{3-4}  & & & & \\ \cline{1-1} \cline{3-4}  & & & & \\ \cline{1-1} \cline{3-4}  & & & & \\ \hline \hline \end{tabular}
\end{table}
Table 3: Summary of related works.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Approach** & **Ref.** & **Solution Summary** & **Benefits and Drawbacks** \\ \hline \multirow{8}{*}{[18]} & \(\bullet\) & Proposes to use fuzzy logic to reduce redundant HOs and HOF rates in dense small cell networks & Benefits: \\  & \(\bullet\) & Analyzes UE velocity and radio channel quality to adapt hysteresis margins for HO decisions & \(\bullet\) & Reduced HOs, HOF, and \\  & \(\bullet\) & Proposes to use ML and data mining techniques to learn and identify cell characteristics and then optimize the HO parameters & \(\bullet\) & Good throughput \\  & \(\bullet\) & The considered HO parameters are A2 and A3 handover thresholds, and TTT period & \(\bullet\) & Low latency \\ \cline{2-4}  & \(\bullet\) & Proposes a GRU-based scheme to predict the number of users in a cell for a given time of day & \(\bullet\) & No results on HOF, number of HOs, and ping-pong rates \\  & \(\bullet\) & The prediction is used for varying cell sizes, making it easier for UEs to be handed over to underloaded cells or harder for UEs to connect to overloaded cells & \(\bullet\) & Benefits: \\  & \(\bullet\) & Proposes a hybrid VAR-GRU scheme to predict the future trajectories of users in a mobile network & \(\bullet\) & Benefits: \\  & \(\bullet\) & The prediction is applied to HO management to reduce HO processing and transmission costs & \(\bullet\) & Higher prediction accuracy than GRU, RNN, and LSTM \\ \hline \multirow{8}{*}{[21]} & \(\bullet\) & Proposes a CoMP transmission scheme and a HO management scheme for HCSNets with macro and small cells & \(\bullet\) & News HO signaling overhead Drawbacks: \\  & \(\bullet\) & Determines if UEs can handover from macro to small cells based on their speed/latency requirements & \(\bullet\) & No other metrics evaluated Mainly focuses on macro-to-small cell HOs \\ \cline{2-4}  & \(\bullet\) & Proposes an EAC scheme for reducing HO preparation & Benefits: \\  & \(\bullet\) & Reduced HO preparation time in cloud RAN & \(\bullet\) & Reduced HO preparation time and overall latency \\ \cline{2-4}  & \(\bullet\) & Focuses on synchronous HO that enables predictable and fast HO to support URLLC services in high mobility applications & \(\bullet\) & Drawbacks: \\ \cline{2-4}  & \(\bullet\) & Proposes a LSTM scheme for reducing HO preparation time in cloud RAN & \(\bullet\) & Only uses cloud; may improve latency by utilizing MEC \\ \cline{2-4}  & \(\bullet\) & Proposes a LSTM scheme for reducing HO preparation time in cloud RAN & \(\bullet\) & \(\bullet\) \\ \cline{2-4}  & \(\bullet\) & Recover the time of the  
In summary, this discussion of related works shows that research gaps that can be addressed still exist. Despite our exhaustive search, very few works on multi-tier handover were found to combine all three approaches above. This presented a unique opportunity for us to explore and propose a new mechanism for multi-tier handover.