# Context-Aware Enhanced Application-Specific Handover in 5G V2X Networks
### Problem Definition and Main Contributions  
The use of 5G V2X networks promises to address the high mobility demands of UE, especially in terms of seamless handover performance. However, this promise comes with a number of complexities, and despite advancements in architecture and resource allocation, mobility management presents notable issues, particularly in terms of UE application usage. Augmented Reality (AR) has been touted as one of the potential solutions that can boost driving experience and safety. Using this technology, however, increases the complexities of high mobility that largely impact the handover processes, leading to increased latency and unnecessary handovers, as well as failures and ping-pong effects. Due to the limitations of traditional HO that have been significantly highlighted by recent studies, HO algorithms must be improved or enhanced to adapt to dynamic network conditions in high-speed V2X networks. Current HO techniques rely profoundly on signal strength-based measurements, which are proven to be insufficient in addressing the varied QoS requirements of vehicular applications such as AR and autonomous driving. High-speed UEs trigger frequent and unnecessary Hos, which is typical in dense 5G networks with a high number of SC deployments, leading to performance degradation. These issues significantly call for an intelligent HO solution that leverages the use of real-time user-specific context information in a predictive modeling approach to alleviate negative effects.  
The gaps that have been presented highlight the need for a novel method that utilizes rich contextual information from UEs, specifically application data, that intelligently inform handover decisions. An enhanced handover mechanism that integrates application contexts such as AR and network parameters such as signal metrics, UE speed, and SC load into a Multiple Criteria Decision-Making (MCDM) model will result in a more holistic and informed HO decision.  
The main contributions of this paper are discussed as follows:  
* A user context-aware process is proposed that considers the service requirements (connection context) of UEs in a dynamic, high-density network environment to optimize handovers while considering basic services such as conversation, video streaming, general traffic (browsing), offloading data, relay services, and advanced technologies such as AR.
* The appropriate assignment of weight-to-criteria parameters in MCDM remains an open issue [7]. It is recommended that the weighting should be dynamically assigned in accordance with the network topology changes. In our proposed MCDM-based HO procedure, we consider the dynamic assignment of weights to an individual network connection quality metric based on network type, and the connection context policy is provided.
* The enhancement of network performance is addressed by reducing the number of handover issues for specific V2X applications. To the best of our knowledge, there is currently no existing study that examines the handover issues for 5G V2X while using AR applications.
* The simulation findings indicate that the proposed method maintains consistent performance across different UE speeds, owing to the effective selection of cells that are adaptable to the diverse needs of the network QoS compared to the recent study in [8].  
The remainder of this paper is organized as follows. Section 2 discusses related work and highlights the solutions and improvements. Sections 3 and 4 discuss the proposed algorithm and findings, respectively. Finally, the conclusions are presented in Section 5.