Computation offloading balance in small cell networks with mobile edge computing

As a promising way to offset the low computation capacity of user equipments (UEs), mobile edge computing (MEC) has attracted great attention of academy and industrial recently. By deploying MEC servers in small cell networks, the communication rate and computation speed could be enhanced efficiently. However, due to the different computation capability of various small cell base stations, micro base stations and UEs, the computation offloading balance becomes a challenging problem. Furthermore, the wireless channel condition and transmission delay also take important roles in the computation offload. In this paper, we jointly consider the spectrum allocation and computation offload selection to achieve desired balance in small cell networks with MEC. In this process, we formulate the spectrum allocation factor, computation offloading decision and UEs’ transmission power as an optimization problem with the objective of minimizing the energy consumption and the constraints of each UE’s latency. Then, we propose a two-step solution algorithm to solve the formulated problem. Finally, simulation results are presented to show the effectiveness of the proposed scheme in the performance of energy consumption, latency, computation offloading ratio and convergence.