## 4 Resource Management in Heterogeneous Network (RM HetNet)
### User Association (UA)
#### 4.2.2 Data Rate  
The data rate measures user association decisions as a performance indicator. By selecting one or more of the BSs to associate with, each UE received the required data rate from a BS, which can guarantee their minimum required rates. In [107], the authors investigated a joint UA and channel allocation problem of a fog radio access network in the uplink scenario. A novel joint UA and channel allocation scheme are developed in order to accomplish the ultra-low latency goal. Within this scheme, the BS is grouped with a user-centric perspective. The delay performance has been significantly enhanced in terms of the control signaling technique and the data transmission procedure. In particular, the multiple access interference between users is examined, and a closed-form equation for the effective rate of a typical user with several BS connections and arbitrary interfering users is developed. The proposed joint UA and channel allocation method considers multiple access interference and guarantees a delay probability. The proposed joint UA and channel allocation strategy effectively addressed statistical delay provisioning issues in HetNet scenarios through simulation. However, access points used high transmission power to serve the network users. Hence, EE needs more attention and consideration. In [108], the authors investigated a joint UA and resource allocation problem of cluster-based energy efficiency in BSG HetNets. The authors aimed to enhance the system EE and reduce the total interference. First, to determine the cluster center and the total number of clusters, they used an enhanced clustering technique that combines the max-min distance clustering algorithm with the K-means clustering algorithm. The intra-cluster interference is then reduced using orthogonal resource allocation within the same cluster. A non-convex issue may be transformed into a convex optimization problem by iteratively optimizing and relaxing the variable. Finally, this article proposed a solution by introducing the joint data rate-based user association and resource allocation algorithm. They presented UA and derived the network utility function through the Lagrange multiplier approach, with users preferring to associate the SBS with the largest utility function result due to interference from SBSs in other clusters. The simulation results illustrated that the proposed algorithm improved the EE and minimized the total interference. However, the tradeoff between EE and SE is not considered. To maximize the total rate of users in the cell of different links while minimizing interference and guaranteeing QoS requirements, the authors in [109] evaluated a joint power allocation and user association using non-cooperative game theory under QoS constraints. The UA is based on the minimum QoS requirement and data rate. To accomplish this goal, they divided the problem into two sub-problems. The backhaul game is the first sub-problem, wherein leaders select their optimal power allocation strategies by finding the optimal strategies of their followers. The second game is called the access game, and its objective is for the followers to provide the best response possible to the leaders. Compared to the hierarchical game, their approach performs better in simulations. Numerical results show that the algorithm effectively ensures dynamic UE association, a higher total rate for all UEs, and throughput stability between backhaul and access links. Nonetheless, EE and frequency allocation is needed more attention and consideration. In [110], the authors investigated a joint user association and power allocation problem of NOMA-based 5G HetNet. A theory-based contract method is presented to handle the imperfect CSI. In order to associate users with BSs in an iterative and distributed way, a reinforcement learning (RL) based technique is chosen, making use of the offered feedback from the communication environment.