  In this paper, we consider the sum power minimization problem via jointly
optimizing user association, power control, computation capacity allocation and
location planning in a mobile edge computing (MEC) network with multiple
unmanned aerial vehicles (UAVs). To solve the nonconvex problem, we propose a
low-complexity algorithm with solving three subproblems iteratively. For the
user association subproblem, the compressive sensing based algorithm is
accordingly is proposed. For the computation capacity allocation subproblem,
the optimal solution is obtained in closed form. For the location planning
subproblem, the optimal solution is effectively obtained via one-dimensional
search method. To obtain a feasible solution for this iterative algorithm, a
fuzzy c-means clustering based algorithm is proposed. Numerical results show
that the proposed algorithm achieves better performance than conventional
approaches.
