Energy Efficient Resource Allocation in UAV-Enabled Mobile Edge Computing Networks
Queen Mary University of London · King's College London · +1 more institution
Abstract
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 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…
Citation impact
- FWCI
- 466.88
- Percentile
- 100%
- References
- 55
Authors
4- ZYZhaohui YangCorresponding
Queen Mary University of London, King's College London, Northumbria University
- CPCunhua Pan
Queen Mary University of London, King's College London, Northumbria University
- KWKezhi Wang
Queen Mary University of London, King's College London, Northumbria University
- MSMohammad Shikh‐Bahaei
Queen Mary University of London, King's College London, Northumbria University
Topics & keywords
- Computer science
- Mathematical optimization
- Mobile edge computing
- Resource allocation
- Iterative method
- Computation
- Cluster analysis
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