# A Survey on 5G Coverage Improvement Techniques: Issues and Future Challenges
## 3 5G Coverage Enhancement Techniques
### 5G Optimization Algorithms
\begin{table}
\begin{tabular}{p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline \hline
**Author \& Ref. No.** & **Approach** & **Advantages** & **Limitations** \\ \hline \multirow{6}{*}{[PERSON] et al. [185]} & \multirow{6}{*}{A genetic algorithm is proposed to optimise the location identification of the mobile station in a cell and new BS deployment location.} & Optimization of the mobile station in a deployment location enhanced cellular network. & \multirow{6}{*}{Deploying new BSs in a cell density area leads to high positioning errors.} \\ \cline{3-3}  & Game theory based algorithm is used in D2D link pairs, to offload the data of one UE to another UE based on the offload coefficient. A Nash bargaining solution is considered to provide a game optimal solution. & Enhanced the energy efficiency and throughput by maximising the high D2D link fairness. The proposed method effectively offloads the UE data. & Energy efficiency decreases with the increase of minimum transmission power required, i.e., at 10 Mbps the energy efficiency is 26.56 and at 50 Mbps it is 24.21. \\ \hline \multirow{6}{*}{[PERSON], [PERSON] et al. [187]} & \multirow{6}{*}{An innovative RL and neural network based scheduling algorithm is proposed to minimise the packet delay and drop rates by maintaining minimum QoS requirements.} & The proposed algorithm and reduced the packet delay. & \multirow{6}{*}{The proposed algorithm enhanced the packet delays.} & \multirow{6}{*}{The energy efficiency decreases with the increase of minimum transmission power required, i.e., at 10 Mbps the energy efficiency is 26.56 and at 50 Mbps it is 24.21. \\ \hline \multirow{6}{*}{[PERSON] et al. [188]} & \multirow{6}{*}{Higher order sectorization with proper antenna tilt is considered to enhance the coverage and capacity in 5G networks.} & \multirow{6}{*}{The proposed model enhanced the indoor and outdoor coverage area.} & \multirow{6}{*}{\
\begin{tabular}{} \end{tabular} } \\ \cline{3-3}  & A new antenna has been proposed to optimise the antenna tilt and beam-forming antennas. & & \\ \cline{3-3}  & The proposed model assumed that the antenna height at the BS should be less than the average height of the high rise buildings in order to enhance the coverage. & The proposed model enhanced the indoor and outdoor coverage area. & \multirow{6}{*}{
\begin{tabular}{} \end{tabular} } \\ \cline{3-3}  & & & \\ \cline{3-3}  & & & \\ \cline{3-3}  & & & \\ \cline{3-3}  & & & \\ \cline{3-3}  & Two RL based algorithms, deep Q-learning based on artificial neural networks and stochastic cellular learning, are used to optimise the antenna tilt. & Enhanced the overall coverage and data rates of a cellular network using two algorithms. ANN enhanced the cell edge performance compared to the stochastic method. & Handovers will increase the cell rejection ratio, which will affect the overall system performance. \\ \hline \multirow{6}{*}{[PERSON], [PERSON] et al. [192]} & Deep deterministic policy gradient and RL algorithms are used to enhance the coverage capacity and to minimise the interference by jointly optimising the antenna tilt and transmit power. & The proposed algorithms enhanced the coverage and capacity of a cellular network. & Automated optimisation techniques are required to predict the actual traffic density and coverage gaps. \\ \cline{3-3}  & & & \\ \cline{3-3}  & & & \\ \cline{3-3}  & & & \\ \cline{3-3}  & Deep deterministic policy gradient and RL algorithms are used to enhance the coverage capacity and to minimise the interference by jointly optimising the antenna tilt and transmit power. & The proposed algorithms enhanced the coverage and capacity of a cellular network. & Automated optimisation techniques are required to predict the actual traffic density and coverage gaps. \\ \hline \hline \end{tabular}
\end{table} 
Table 16: Summary of optimization algorithms used to enhance the coverage and capacity of 5G networks.