In heterogeneous cellular network, task scheduling for computation offloadingis one of the biggest challenges. Most works focus on alleviating heavy burdenof macro base stations by moving the computation tasks on macro-cell userequipment (MUE) to remote cloud or small-cell base stations. But theselfishness of network users is seldom considered. Motivated by the cloud edgecomputing, this paper provides incentive for task transfer from macro cellusers to small cell base stations. The proposed incentive scheme utilizes smallcell user equipment to provide relay service. The problem of computationoffloading is modelled as a two-stage auction, in which the remote MUEs withcommon social character can form a group and then buy the computation resourceof small-cell base stations with the relay of small cell user equipment. Atwo-stage auction scheme named TARCO is contributed to maximize utilities forboth sellers and buyers in the network. The truthful, individual rationalityand budget balance of the TARCO are also proved in this paper. In addition, twoalgorithms are proposed to further refine TARCO on the social welfare of thenetwork. Extensive simulation results demonstrate that, TARCO is better thanrandom algorithm by about 104.90% in terms of average utility of MUEs, whilethe performance of TARCO is further improved up to 28.75% and 17.06% by theproposed two algorithms, respectively.
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