This study presents a high-fidelity digital twin (DT) framework designed to evaluate and improve vertiport operations for Advanced Air Mobility (AAM). By integrating Unreal Engine, AirSim, and Cesium, the framework enables real-time simulation of Unmanned Aerial Vehicles (UAVs), including unmanned electric vertical take-off and landing (eVTOL) operations under nominal and disrupted conditions, such as adverse weather and engine failures. The DT supports interactive visualisation and risk-free analysis of decision-making protocols, vertiport layouts, and UAV handling strategies across multi-scenarios. To validate system realism, mixed-reality experiments involving physical UAVs, acting as surrogates for eVTOL platforms, demonstrate consistency between simulations and real-world flight behaviours. These UAV-based tests confirm the applicability of the DT environment to AAM. Intelligent algorithms detect Final Approach and Take-Off (FATO) areas and adjust flight paths for seamless take-off and landing. Live environmental data are incorporated for dynamic risk assessment and operational adjustment. A structured capacity evaluation method is proposed, modelling constraints including turnaround time, infrastructure limits, charging requirements, and emergency delays. Mitigation strategies, such as ultra-fast charging and reconfiguring the layout, are introduced to restore throughput. This DT provides a scalable, drone-integrated, and data-driven foundation for vertiport optimisation and regulatory planning, supporting safe and resilient integration into the AAM ecosystem.

The aviation and air mobility sector are experiencing a profound evolution, fuelled by swift technological progress and escalating requirements for effective, secure, and dependable airborne communication frameworks. The integration of Unmanned Aerial Systems (UAS), such as drones, into commercial and logistical activities is revolutionizing traditional concepts of air mobility. Integrating the Carrier Sense Multiple Access/Collision Avoidance (CSMA/CA) protocol into UAS communication networks enhances safety and reliability by preventing collisions. CSMA/CA allows UAS to sense the communication medium's availability before transmitting data, minimizing the risk of collisions and ensuring efficient data transmission, cru-cial for scenarios where safety is paramount. Sixth-Generation (6G) technology coupled with CSMA/CA protocol integration strengthens reliability and effectiveness in ensuring safe and efficient UAS operations. Simulation analysis using MATLAB helps understand signal quality and latency variations with distance from the UAV to the receiver, essential for safety communications analysis. Analyzing handover procedures is crucial for public safety, especially in scenarios where UAS encounter situations requiring a change from one base transceiver station (BTS) to another. Vertical handovers, particularly relevant in the context of evolving Unmanned Traffic Management (UTM) and Air Traffic Management (ATM) architectures, may become more prevalent due to the significant altitude variations inherent in UAS operations.

In the realm of modern aerospace communications, the integration of Unmanned Aerial Vehicles (UAVs) with Low Earth Orbit (LEO) satellite constellations can offer a transformative solution for enabling Beyond Visual Line of Sight (BVLOS) operations. Due to initial safety operation demand of UAV BVLOS communication new metrics, this paper proposes a new quality of service (QoS) framework for uplink communication between IRIDIUM satellite constellation and UAV. The objective is to benchmark key QoS metrics for UAVLEO communications using a Non-Terrestrial Network (NTN) narrowband (NB) channel. However, this study performs metrics such as latency and throughput across various elevation angles and environments. Different sample rates are evaluated to assess their impact on communication performance. Simulation analysis indicate that lower sample rates provide reduced latency and stable throughput suitable for telemetry, while higher sample rates increase throughput at the cost of higher latency. This study can be a road map for QoS metrics for optimizing satellite communication systems in UAV operations and demonstrates optimal communication for BVLOS missions in rural, suburban and underserved areas where ground infrastructure is limited. The findings are compared against current standards and regulatory benchmarks for validation.

Next-generation aviation demands seamless connectivity across heterogeneous networks, yet maintaining uninterrupted links under strict performance requirements remains a major challenge. Current Aeronautical Telecommunication Network (ATN) mechanisms depend on static tables that overlook airframe shadowing and dynamic flight conditions, limiting their effectiveness in complex radio environments. This paper delivers a comprehensive evaluation of terrestrial and non-terrestrial networks (NTN) and benchmarks twelve link-selection algorithms across representative Air-to-Satellite (A2Sat) and Air-to-Ground (A2G) scenarios. The system design introduces an AI-driven dual-layer onboard controller that integrates predictive planning with real-time adaptation. Simulation results show that this approach enables proactive link switching, enhances stability, and supports efficient flight operations. To sum up, this work can be a roadmap for ATN architectures by delivering resilient, hyper-connected communications required for next-generation aviation and paves the way for this implementation.