## 3 Spectrum Management Issues
### Cognitive Radio  
One of the prominent strategies to attain a high level of spectrum resource optimization required for the current 5G is through a flexible sharing and allocation of available spectrum resources through flexible and opportunistic usage [101]. The existing spectrum regulatory policies do not encourage \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Approach** & **Methodology/Technique** & **Advantages** & **Limitation/Future Work** & **References** \\ \hline \multirow{8}{*}{Resource sharing} & Component Carrier (CC) & Increase network & \multirow{8}{*}{No improvement in fairness index} \\  & selection based on the head of the line delay and threshold delay & throughput and reduce computational complexity & & \\ \cline{1-1} \cline{2-5}  & Design an efficient packet & \multirow{8}{*}{No improvement in fairness index} \\  & scheduling algorithm based on proportional fairness to use in multiple CC’s systems & Support both real and non-real-time traffic & Inefficient when packet traffic is fluctuating & [92] \\ \cline{1-1} \cline{2-5}  & Joint optimization technique & Computational complexity & \multirow{8}{*}{Low fairness index for cell-edge users} & [93] \\  & algorithm for CC selection & is decreased & & \\ \cline{1-1} \cline{2-5}  & Traffic and channel-driven CC & Better performance as compared to least-load & Low fairness index when \\  & selection by considering channel quality and quality indicator & a high number of users & [94] \\  & traffic load & (CQI) algorithm & & \\ \hline \multirow{8}{*}{Energy efficiency} & Relaying scheme to improve the coverage, fairness, and capacity for CA-based system & Work for both intra-and & More advance algorithm is needed for the & [95] \\ \cline{1-1} \cline{2-5}  & The Bisection Method for Energy Minimization & \multirow{8}{*}{Reducing network capacity and improves massive energy saving} & Interference effect due to multiple BSs on the same layer & [96] \\ \cline{1-1} \cline{2-5}  & minimize the energy consumption and capacity & & & \\ \cline{1-1} \cline{2-5}  & maximization & & & \\ \hline \multirow{8}{*}{Capacity improvement} & User scheduling and combined cell association, where the user can connect BSs by using multiple carrier bands & Convex optimization solutions to enhance the network capacity & Computational complexity increases for high users & [97] \\ \cline{1-1} \cline{2-5}  & Cross-layer scheduling approach based on three mechanisms: (1) Markov Decision Process-Based Cost & \multirow{8}{*}{Better results for capacity, network reward, and packet failure rate} & An analytical method is needed for centralized radio access network & [98] \\ \cline{1-1} \cline{2-5}  & Reward Packet Selection (MDP-PS), (2) Adaptive Packet Scheduling (APS), and (3) Adaptive Component Carrier & \multirow{8}{*}{Support both inter-band and intra-band} & \multirow{8}{*}{L Limited to single-Input-Multiple-Output (SIMO) scenario only} & \\ \cline{1-1} \cline{2-5}  & Scheduling (ACC) & & & \\ \hline \multirow{8}{*}{Transmission performance} & Receiver design architecture based on cascade-shutoff Low-Noise Transconductance Amplifier (LNTA) & Support both inter-band and intra-band & Limited to single-Input-Multiple-Output (SIMO) scenario only & [99] \\ \cline{1-1} \cline{2-5}  & A latency-efficient Code-Division Multiplexing (CDM) CA approach based on least-squares approximation & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Summary of the related work for Carrier Aggregation (CA). flexible frequency utilization and opportunistic spectrum access in the cellular systems. Recently, the FCC has committed to the implementation of the shared utilization of the 3550-3650 MHz bands [102]. CR, based on a software-defined radio, offers the opportunity for flexible spectrum access in wireless systems [103]. It is also regarded as one of the key players of the current 5G cellular network. CR work is classified into three main sections, namely, spectrum management, intelligence management, and interference management [104].