# Handover Decisions for Ultra-Dense Networks in Smart Cities: A Survey
###### Abstract
In addition, while there are several review papers on handover mechanisms [1; 7], most of them provide a shallow overview of different methodologies without presenting a systematic approach to categorizing studies based on methodologies, techniques, and application fields. The existing literature overlooks the interaction between influential factors such as mobility management, security, and QoS evaluation within HO decision-making [7]. This lack of structure means that it is challenging to identify gaps in current research, i.e., overlooked metrics or performance measures. Few review articles even consider the trajectory of HO research along temporal scales or provide insights on avenues for future work or on new trends. The absence of graphical representation of research trends, and predictive forecasting of how HO techniques would evolve in 6G networks, constrains the ability of researchers and industry professionals to predict major challenges and opportunities in this topic. In addition, while industry reports often highlight network performance shortcomings, few academic studies assess cascading failures rigorously. For example, the effect of network congestion or infrastructure damage on HO efficiency is seldom quantified. It is necessary to analyze such potential risks to develop efficient and resilient HO mechanisms in 6G networks [8; 9]. Security is another important concern in 6G network HO management. The relentless HO of devices from one access point to another introduces latent vulnerabilities that are easily targeted by malicious actors. Threats such as HO fraud, man-in-the-middle attacks, and DoS attacks put the integrity of the network at serious risk. Traditional security protocols can be ineffective in the presence of such threats, so recourse is taken in the form of blockchain-based authentication, AI-driven anomaly detection, and quantum cryptography for HO procedure security. Moreover, privacy-preserving approaches such as federated learning can be employed to enable secure data-driven HO decision-making without revealing sensitive user information. Implementation of such security protocols is essential to establish trust and reliability for 6G networks, particularly when financial transactions, healthcare, and autonomous systems are concerned [10]. Although significant advancements have been made in HO research for 4G and 5G networks, the study of HO mechanisms in 6G is in its early stages. Most of the current work has been on mobility management problems in ultra-dense 4G and 5G scenarios, with a focus on high-frequency handovers, reducing ping-pong effects, and optimizing resource allocation. But challenges of 6G networks, including the use of higher frequency bands, AI-based decision-making, and unifying heterogeneous network infrastructure, introduce new complexities that require further study. While existing HO techniques provide the basic knowledge, they are not sufficient to address the unique demands of 6G, where smart and dynamic decision-making prevails. This research gap emphasizes the necessity of an extensive study of HO management strategies specifically for 6G networks. An extensive study of novel HO mechanisms with AI-based methods, deep learning-based mobility prediction, and real-time data processing will be responsible for ensuring seamless mobility as well as efficient utilization of network resources. Another significant aspect that has not been explored well is the impact of energy efficiency in HO decision-making [11]. With the projected increase in device connectivity and ultra-dense network deployment, energy consumption optimization in HO procedures will be the standard. Current HO mechanisms are primarily designed to provide connectivity and reduce latency at the expense of energy efficiency. However, 6G networks will need to balance these factors using energy-efficient HO techniques that maintain power consumption at a minimum without compromising QoS.