Improving Connectivity in 6G Maritime Communication Networks With UAV Swarms

Abstract

The deployment of maritime communication networks (MCNs) enables Internet-of-Things (IoT) applications, related to autonomous navigation, offshore facilities and smart ports. Still, the majority of maritime nodes, residing in MCNs lacks reliable connectivity. Towards this end, integrating unmanned aerial vehicles (UAVs) in sixth generation (6G) MCN topologies results in the formation of an aerial segment, complementing shore base stations that may offer insufficient coverage, and satellite communication, characterized by increased delays. In this study, we focus on an MCN where the direct links towards a shore BS are not available, due to excessive fading conditions. For this case, we use a UAV swarm to provide improved wireless connectivity, adopting non-orthogonal multiple access (NOMA) for high resource efficiency. In downlink communication, UAVs take into consideration the desired service rate and the channel quality of their links towards the maritime nodes. In the uplink, UAVs employ dynamic decoding ordering to enhance the performance of successive interference cancellation, avoiding fixed ordering of the maritime nodes’ signals. Moreover, to ensure highly flexible UAV selection, UAVs are equipped with buffers to store data. Performance comparisons show that the UAV swarm-aided MCN enjoys increased average sum-rate by relying on multi-criteria-based interference cancellation and buffer-aided UAVs, over other benchmark schemes in the downlink and uplink. Finally, the delay-aware nature of the proposed algorithms where the UAV-destination links are prioritized, leads to reduced average delay.

Keywords

• 6G
• buffer-aided
• maritime communication network (MCN)
• maritime IoT
• NOMA
• swarms