## 4 Resource Management in Heterogeneous Network (RM HetNet)
### Power Allocation (PA)
#### 4.1.1 Throughput  
System throughput, measured in bits per second, is the aggregate data rate transmitted successfully across all nodes in a network. Throughput optimization methods are discussed in this section. In [82], the authors consider the power allocation problem in heterogeneous networks. They proposed a dynamic optimization model to minimize the total power of HetNets and provide network capacity and coverage. Energy consumption has been considered to balance capacity and power to ensure QoS constraints. The proposed model determines when small cells with the highest energy efficiency should be turned ON or OFF in order to optimize power utilization. The simulation results showed significant power savings in different scenarios while ensuring the throughput constraints for network users. Furthermore, data rates and energy efficiency are significantly improved. Nonetheless, the delay constraints of the proposed model are not considered. In [83], the authors investigated a power optimization strategy for interference management in 5G HetNets comprised of macrocells and underlying femtocells. They proposed a game theoretic power control strategy to find a user-specific optimum transmission power. The user, acting as a player, selects a power level and is rewarded according to the signal-to-interference noise ratio (SINR) that is probably received. Users compete for the highest payoff while also meeting their quality-of-service demands. Then, they developed an algorithm based on iterative learning to integrate the power optimization game. In multiple iterations of the algorithm, the optimal power allocation for all users yields decreased interference. The proposed mechanism is effective in numerical simulations for increasing throughput, guaranteeing the quality of service, and reducing interference. Nevertheless, imperfect channel state information impact requires attention and consideration. In [84], the authors considered a coordinated multi-point scenario in HetNet, which is a cooperative technology between BSs to reduce interference. Furthermore, the investigated scenario prevents severe interference at the cell edges by forming links while considering each cell load. The channel gain between the user and the base station was used as a criterion for power allocation. In order to decrease interference power, this allocation scheme distributed subcarriers orthogonal to the nearby UEs and increased the distance between users who shared a single subcarrier. The simulation results demonstrated that the proposed method improved the total sum rate by effectively decreasing the interference between the neighboring clusters. However, the system energy efficiency of the proposed scheme is not considered. In [85], to achieve joint optimization regarding throughput and EE for imperfect channels encountered in high-speed railway communication, the authors proposed a power allocation interference alignment algorithm based on game equilibrium. They developed a game model and demonstrated the existence of Nash equilibrium to increase system throughput and decrease energy consumption. Moreover, a recurrent neural network-based iterative algorithm for PA was proposed. When the optimal power matrix is calculated iteratively and combined with the maximal SINR interference alignment algorithm, interference management optimization is achieved. The algorithm is well-suited for a high-speed heterogeneous network, and simulation results demonstrate its effectiveness in boosting energy efficiency, throughput, and reliability in a realistic imperfect channel state information (CSI) scenario for a high-speed railway. Nonetheless, the handover effect requires