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We consider a heterogeneous network with mobile edge computing, where a usercan offload its computation to one among multiple servers. In particular, weminimize the system-wide computation overhead by jointly optimizing theindividual computation decisions, transmit power of the users, and computationresource at the servers. The crux of the problem lies in the combinatorialnature of multi-user offloading decisions, the complexity of the optimizationobjective, and the existence of inter-cell interference. Then, we decompose theunderlying problem into two subproblems: i) the offloading decision, whichincludes two phases of user association and subchannel assignment, and ii)joint resource allocation, which can be further decomposed into the problems oftransmit power and computation resource allocation. To enable distributedcomputation offloading, we sequentially apply a many-to-one matching game foruser association and a one-to-one matching game for subchannel assignment.Moreover, the transmit power of offloading users is found using a bisectionmethod with approximate inter-cell interference, and the computation resourcesallocated to offloading users is achieved via the duality approach. Theproposed algorithm is shown to converge and is stable. Finally, we providesimulations to validate the performance of the proposed algorithm as well ascomparisons with the existing frameworks.

Decentralized Computation Offloading and Resource Allocation in Heterogeneous Networks with Mobile Edge Computing