  Multi-access edge computing (MEC)-enabled integrated space-air-ground (SAG)
networks have drawn much attention recently, as they can provide communication
and computing services to wireless devices in areas that lack terrestrial base
stations (TBSs). Leveraging the ample bandwidth in the terahertz (THz)
spectrum, in this paper, we propose MEC-enabled integrated SAG networks with
collaboration among unmanned aerial vehicles (UAVs). We then formulate the
problem of minimizing the energy consumption of devices and UAVs in the
proposed MEC-enabled integrated SAG networks by optimizing tasks offloading
decisions, THz sub-bands assignment, transmit power control, and UAVs
deployment. The formulated problem is a mixed-integer nonlinear programming
(MILP) problem with a non-convex structure, which is challenging to solve. We
thus propose a block coordinate descent (BCD) approach to decompose the problem
into four sub-problems: 1) device task offloading decision problem, 2) THz
sub-band assignment and power control problem, 3) UAV deployment problem, and
4) UAV task offloading decision problem. We then propose to use a matching
game, concave-convex procedure (CCP) method, successive convex approximation
(SCA), and block successive upper-bound minimization (BSUM) approaches for
solving the individual subproblems. Finally, extensive simulations are
performed to demonstrate the effectiveness of our proposed algorithm.
