  In the coming smart ocean era, reliable and efficient communications are
crucial for promoting a variety of maritime activities. Current maritime
communication networks (MCNs) mainly rely on marine satellites and on-shore
base stations (BSs). The former generally provides limited transmission rate,
while the latter lacks wide-area coverage capability. Due to these facts, the
state-of-the-art MCN falls far behind terrestrial fifth-generation (5G)
networks. To fill up the gap in the coming sixth-generation (6G) era, we
explore the benefit of deployable BSs for maritime coverage enhancement. Both
unmanned aerial vehicles (UAVs) and mobile vessels are used to configure
deployable BSs. This leads to a hierarchical satellite-UAV-terrestrial network
on the ocean. We address the joint link scheduling and rate adaptation problem
for this hybrid network, to minimize the total energy consumption with quality
of service (QoS) guarantees. Different from previous studies, we use only the
large-scale channel state information (CSI), which is location-dependent and
thus can be predicted through the position information of each UAV/vessel based
on its specific trajectory/shipping lane. The problem is shown to be an NP-hard
mixed integer nonlinear programming problem with a group of hidden non-linear
equality constraints. We solve it suboptimally by using Min-Max transformation
and iterative problem relaxation, leading to a process-oriented joint link
scheduling and rate adaptation scheme. As observed by simulations, the scheme
can provide agile on-demand coverage for all users with much reduced system
overhead and a polynomial computation complexity. Moreover, it can achieve a
prominent performance close to the optimal solution.
