6G Technologies for Maritime Communication Networks

In recent decades, wireless networks have been evolving towards supporting users and services that are located in urban environments, while the fourth and fifth generations (4G and 5G) of mobile communications have put special emphasis in the coexistence of mobile users and Internet-of-Things (IoT) devices. Nonetheless, most network architectures and communication techniques were designed for land-based communications, while maritime communication networks (MCNs) have been largely neglected from this revolution. As a result MCNs are mainly supported by the satellite segment, with the well-known issues of high-latency and low-data rates. The vast majority of trade relies on maritime transportation, while there has also been a spike in interest for a wide range of maritime activities such as pollution monitoring and ocean exploration for natural resources. Therefore, a radical shift to maritime communications is needed.

The 6G era calls for the integration of state-of-the-art technologies in MCNs, including multi-modal RF/free-space optical/visible light/acoustic communication, artificial intelligence and machine learning, unmanned vehicles (aerial, surface, underwater) and edge computing and caching. In this way, integrated MCN architectures will be formed, comprising satellite-aerial-shore-sea surface and underwater segments, enabling novel applications for users, vessels and machines with diverse QoS requirements.

The purpose of this Research Topic is to provide an overview of the status of 6G technologies for maritime communication networks. Prospective authors are invited to submit original manuscripts on topics including, but not limited to:

• Intelligent reflecting surfaces-aided MCNs
• Multi-modal communication with RF/free-space optical/visible light/acoustic communication schemes
• Physical layer security techniques for MCNs
• Integrated sensing and communication for MCNs
• Multi-hop relaying techniques for MCNs
• Measurements and channel modeling for MCNs
• Radio resource management algorithms for MCNs
• Non-orthogonal multiple access schemes for MCNs
• Machine-learning-aided optimization for MCNs
• Integrated satellite-UAV-terrestrial network architecture for MCNs
• UAV-aided MCNs
• Swarm intelligence in MCNs with aerial, surface, underwater vehicles
• Trajectory optimization for unmanned vehicles-aided MCNs
• Mobile edge computing and caching for MCNs
• Software-defined network architectures for MCNs
• Experimental studies and test-beds