Joint Computation Offloading and Variable-width Channel Access Optimization in UAV Swarms

Abstract

Device-to-device (D2D)-enabled mobile edge computing (MEC) is an emerging technology which has been widely investigated in terrestrial networks. Different from most existing relevant work, where the network is base station-assisted and offloadings are made on homogeneous channels, this paper focuses on an unmanned aerial vehicle (UAV) swarm, where both the decentralized character and the heterogeneous data computation demands are considered. To fully utilize the limited time, spectrum and computation resources, the joint computation offloading and variable-width channel access problem is investigated. The problem is solved by a game-theoretic based solution. Specifically, the problem is first formulated into a game model which is proved to be an exact constrained potential game (ECPG). The game has at least one pure strategy generalized Nash equilibrium (GNE) and the best GNE is the global optimum of the problem. After that, to enable the UAV swarm reach the GNE autonomously, a distributed collective best response (COBR) algorithm is then proposed. The algorithm can converge to a GNE of the game, which is the local or global optimum of the proposed problem. Simulation results show that the proposed method can save about 10% energy than offloading on homogeneous channels.