# A Survey of Handover Management in Mobile HetNets: Current Challenges and Future Directions
## 2 Related Surveys  
Several survey papers have been published on the topic of handover and mobility management in mobile HetNets. The authors provided a detailed overview of the handover and mobility issues in the burgeoning ultra-dense mobile networks in [21]. They discussed the key findings from recent studies, highlighted the technical difficulties and potential opportunities related to mobility from the perspective of developing ultra-dense cellular networks. They not only presented a thorough tutorial on 5G mobility approaches, but also highlighted the key mobility risks of legacy networks. An overview of the handovers and mobility management utilizing 5G enabling technologies is provided in [22]. They described the 5G wireless network layout and explored HO information gathering and decision management methods for ultra-dense small cell networks, with a particular emphasis on how machine learning approaches can assist in optimizing the HO process in 5G networks. Additionally, they addressed the HO information gathering techniques, radio resource control, HO metrics, and categorization of HO decision systems. In the survey by [23], the authors provided an overview of the current state of cellular communication networks. They then provided a comprehensive tutorial on mobility and handover management in 5G, emphasizing the unique challenges posed by its features such as mmWave communications, HetNets, IoT, vehicular communications, device-to-device communications (D2D), and high-speed train communications, which are more complex than in 4G. Additionally, they discussed the basics of handover management in B5G and 6G THz communications. They also discussed the main branches of ML, including supervised, unsupervised, and reinforcement learning (RL), and how each is applied to the handover management process. They provided a thorough analysis of recent research on ML-assisted handover management methods under a novel classification based on the two major categories of visual data-based and wireless network data-based handover management methods. In the survey paper [24], the authors provided an overview of SON functions and its various definitions. They discussed the major categories of SON and highlighted the most well-known applications of SON in 5G cellular networks. They also discussed the different SON architecture designs that aim to make the system more scalable, flexible, and open, and provide more intelligence to the 5G network. The authors emphasized the benefits of using ML and big data to overcome the constraints of SON implementation in 5G networks, while also highlighting the drawbacks and challenges of implementing  
Figure 2: Outline of the Article. SON in 5G cellular networks. They grouped the SON functions based on how 5G mobile networks are managed, and explained the challenges that SON must overcome to be effectively used in 5G networks. The authors of [25] discussed recent research on various handover and mobility management strategies in 5G ultra-dense HetNets, with a focus on dual connectivity (DC). They first provided an overview of the fundamental principles of 5G networks and HO procedures in 5G HetNets. They then examined the use of DC in 5G, highlighting its benefits and drawbacks, as well as the significant challenges that may arise as a result of DC in future networks, such as mobility management, spectrum management, high data rate requirements, and security and privacy. They also explored opportunities and potential solutions to these challenges through the use of AI, ML, and DL techniques and optimization of load and mobility processes. The authors in [26; 27] conducted a comprehensive survey on handover decision making in 4G and 4G/5G networks. They first provided a technical overview of admission control and handover procedures, as well as challenges in handover management in the latest LTE-A architecture. They then analyzed various handover methods and algorithms, focusing on the main approaches and factors used in making handover decisions.