  In modern networks, the use of drones as mobile base stations (MBSs) has been
discussed for coverage flexibility. However, the realization of drone-based
networks raises several issues. One of the critical issues is drones are
extremely power-hungry. To overcome this, we need to characterize a new type of
drones, so-called charging drones, which can deliver energy to MBS drones.
Motivated by the fact that the charging drones also need to be charged, we
deploy ground-mounted charging towers for delivering energy to the charging
drones. We introduce a new energy-efficiency maximization problem, which is
partitioned into two independently separable tasks. More specifically, as our
first optimization task, two-stage charging matching is proposed due to the
inherent nature of our network model, where the first matching aims to schedule
between charging towers and charging drones while the second matching solves
the scheduling between charging drones and MBS drones. We analyze how to
convert the formulation containing non-convex terms to another one only with
convex terms. As our second optimization task, each MBS drone conducts
energy-aware time-average transmit power allocation minimization subject to
stability via Lyapunov optimization. Our solutions enable the MBS drones to
extend their lifetimes; in turn, network coverage-time can be extended.
