# Handover Decisions for Ultra-Dense Networks in Smart Cities: A Survey
###### Abstract  
Handover (HO) management plays a key role in ensuring uninterrupted connectivity across evolving wireless networks. While previous generations such as 4G and 5G have introduced several HO strategies, these techniques are insufficient to meet the rigorous demands of sixth-generation (6G) networks in ultra-dense, heterogeneous smart city environments. Existing studies often fail to provide integrated HO solutions that consider key concerns such as energy efficiency, security vulnerabilities, and interoperability across diverse network domains, including terrestrial, aerial, and satellite systems. Moreover, the dynamic and high-mobility nature of smart city ecosystems further complicate real-time HO decision-making. This survey aims to highlight these critical gaps by systematically categorizing state-of-the-art HO approaches into AI-based, fuzzy logic-based, and hybrid frameworks, while evaluating their performance against emerging 6G requirements. Future research directions are also outlined, emphasizing the development of lightweight AI-fuzzy hybrid models for real-time decision-making, the implementation of decentralized security mechanisms using blockchain, and the need for global standardization to enable seamless handovers across multi-domain networks. The key outcome of this review is a structured and in-depth synthesis of current advancements, which serves as a foundational reference for researchers and engineers aiming to design intelligent, scalable, and secure HO mechanisms that can support the operational complexity of next-generation smart cities. sixth-generation (6G) networks; handover (HO) management; artificial intelligence (AI); machine learning (ML); smart city 2025133  
optimization, 6G is expected to deepen this integration by embedding these technologies as fundamental building blocks for autonomous, real-time, and context-aware network control. In addition, these networks will leverage advanced handover (HO) decision-making algorithms to ensure seamless connectivity in highly dynamic and heterogeneous environments [1; 2]. The management of handover is a natural part of 6G networks with a pivotal role in providing seamless communication as users move from one network node to another. For traditional cellular networks, HO decisions are really based on signal strength thresholds. But such strategies often lead to frequent and unnecessary handovers, which thus contribute to network congestion and overall quality-of-service (QoS) degradation. Ultra-dense small-cell deployment, terrestrial and non-terrestrial network (e.g., satellite and aerial network) integration, and improved user mobility all make HO decision-making more difficult in 6G networks. Hence, efficient HO management is required to reduce latency, optimize the allocation of network resources, and provide uninterrupted service delivery, particularly in smart city environments where real-time communication and automation are crucial [3; 4]. One of the main challenges of HO management in 6G is having to consider the extremely disparate network conditions resulting from the convergence of heterogeneous access technologies. Unlike previous generations that primarily utilized cellular towers for communication, 6G networks will have satellite communications, UAV-assisted networks, and intelligent reflecting surfaces (IRSs). These added elements introduce variables to HO decision-making, and therefore, there is a requirement to create adaptive and AI-driven techniques to effectively manage dynamic network situations. The HO complexity in 6G is additionally augmented by other factors such as vehicular network high-speed mobility, higher interference in high-density areas, and the need for ultra-low-latency services in mission-critical use. The solutions to these problems require a multi-dimensional solution that combines predictive analytics, reinforcement learning, and monitoring of the real-time network state [5; 6].