## 4 Resource Management in Heterogeneous Network (RM HetNet)
### Mode Selection (MS)
#### 4.3.2 Dynamic
The number of user devices and the distance between the BS and the user device are considered when determining the various communication modes. The proposed MS technique significantly improves user throughput over baseline cellular systems, especially in the presence of medium or high UE densities and for users close to the cell edge. The research results of the simulation demonstrated the importance of incorporating accurate information regarding the context of users into the decision-making process to enhance the system's performance. In addition, the results showed that the proposed method could adapt the MS choice it makes in response to different and varying operational conditions within the cell. Nevertheless, user association requires attention and consideration. In [123], the authors discussed the MS problem for D2D communication that is underlaid in a cellular network to improve the system's throughput while simultaneously maximizing user access. They suggested a probabilistic integrated resource allocation approach as well as a quasi-convex optimization technique depending on the probability of channel characteristics. The simulation results demonstrated the efficiency of the communication strategy by showing that the proposed approach can significantly improve system throughput and user experience and eliminate interference between users. In order to maximize system capacity while guaranteeing a fair user experience, all modes consider users' varying channel quality, dynamically choose MS in each scheduling period, and resource allocate blocks. However, the equilibrium between user experience and channel utilization in the proposed approach is not considered. In [124], the authors demonstrated direct D2D communication for 5G and 6G networks operating in dynamic scenarios in which the D2D network topology is subject to the mobility of users. In particular, they thought about a situation where multiple users are located within the coverage area of a single BS and where differences in speed and direction cause changes in the D2D network topology, either through direct connections or via single-hop or multi-hop D2D paths. They formulated a problem to minimize the power consumption of the D2D devices while maximizing the total SE by choosing the optimal transmission mode. In order to solve the above issue, they proposed a distributed AI solution plan that takes into account the mobility of the D2D to create efficient clusters and stable and better backhauling links dynamically. The results showed that an improved distributed AI solution outperformed its related counterparts in terms of SE and power consumption. These alternatives included the distributed sum rate, the distributed random, and the single-hop relay approach. Nonetheless, signaling overhead due to a large number of relays and users is not considered. In [125], the authors proposed a sum-rate maximization model for D2D communication underlaid cellular networks, which simultaneously depends on MS and power control. Joint optimization was utilized to determine the optimal MS and power control, which is a nonconvex problem with both linear and nonlinear requirements. Sub-optimal solutions to the joint optimization method were derived from the Lagrange dual function. They proposed the deep neural network algorithm, which uses the Lagrange dual function as its loss function. The proposed model for a deep neural network is learned in such a way as to reduce the loss function. Deep neural network performance compared to exhaustive search and other suboptimal methods. The results justify the proposed MS model to select the optimal mode (D2D or device-infrastructure-device) for user pairs to improve system performance. Moreover, the results demonstrated that the proposed deep neural network method outperforms the Lagrange duality approach and finds a near-global optimal solution at a much lower computational complexity than an exhaustive search. Nevertheless, imperfect channel state information is not considered in the proposed scenario.