Wireless Communications for Smart Mobility Systems

Dear Colleagues,

The rapid advancement of wireless communication technologies is reshaping modern smart mobility systems (SMS) by enabling seamless connectivity, ultra-reliable low-latency communication (URLLC), and intelligent networks. The next generation of wireless networks, particularly 6G, will play a transformative role in transportation, supporting connected and autonomous vehicles (CAVs), future railway mobile communication systems (FRMCS), and urban aerial mobility (UAM). Emerging wireless communication paradigms—such as millimeter-wave (mmWave) and terahertz (THz) communication, massive MIMO, reconfigurable intelligent surfaces (RIS), and integrated sensing and communication (ISAC)—will be crucial in addressing the stringent requirements of high-mobility environments.

In parallel, artificial intelligence (AI) and machine learning (ML) are transforming the way wireless networks operate in smart mobility applications. In particular, native AI-assisted communications will distinguish 6G networks from the previous wireless generations. A key enabler for an efficient AI-assisted SMS is the deployment of explainable AI (XAI) schemes that aim to explain the logic behind the black-box model behavior of classical AI models, and thus, ensure its efficient and safe deployment. This is due to the critical safety requirements needed to ensure the efficiency of the AI-assisted SMS, where using AI as black-box models is risky and challenging. Hence, it is crucial to understand and trust the decisions taken by these models.

This Special Issue focuses on cutting-edge research in wireless communication for smart mobility, covering areas including but not limited to the following:

1. Wireless Communication Technologies for Smart Mobility Systems
• Fundamental information-theoretical limits for mobility networks.
• Integrated sensing and communication (ISAC) for intelligent transportation.
• Radar-as-a-Service (RaaS) for smart mobility applications.
• Spectrum management and resource reservation for high-mobility environments.
• Channel modeling and propagation studies in V2X, railway, and aerial mobility scenarios.
• MIMO, massive MIMO, and RIS for SMS.
• mmWave and THz communication for SMS.
• Non-terrestrial networks (NTN) and satellite communications for SMS.
• Localization, positioning, and navigation for intelligent mobility.
2. AI-Assisted Solutions for Wireless Smart Mobility Systems
• AI-driven communication architectures for mobility networks.
• Deep learning for channel estimation and interference management.
• Reinforcement learning for network optimization.
• Federated learning for secure and privacy-preserving V2X.
• Explainable AI (XAI) for wireless communication in mobility networks.
• Data fusion and AI-driven decision-making for mobility applications.
3. Security, Privacy, and Sustainability in SMS
• Security and privacy frameworks for connected mobility networks.
• AI-based anomaly detection and cybersecurity in V2X and railway communication.
• Sustainable and zero-energy wireless communication for SMS.
4. Experiments, Prototypes, and Field Trials
• Real-world implementations of next-generation wireless mobility networks.
• Testbeds, experimental platforms, and large-scale trials.

Dr. Shahab Ehsanfar
Dr. Abdulkarim Gizzini
Prof. Dr. Luciano Leonel Mendes
Guest Editors

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• 6G
• AI-assisted SMS
• channel modeling
• FRMCS
• ISAC
• NTN
• THz communication
• V2X
• XAI