Optimal Offloading Strategy and Resource Allocation in SWIPT-based Mobile-Edge Computing Networks

In this paper, we consider a simultaneous wireless information and power transfer (SWIPT)-based mobile edge computing (MEC) system consisting of a multi-antenna access point (AP), multiple single antenna ultra-low power devices (ULPDs) and a MEC server. The objective is to process the information gathered by the ULPDs relying only on the energy obtained through RF energy harvesting (EH). To achieve this, the computation burden is partially assigned to the ULPDs and partially offtoaded to a MEC server. It is assumed that the AP simultaneously delivers power and control signals to the ULPDs by using SWIPT. The ULP network exploits the harvested energy for decoding the control message and either locally computing or offloading the tasks to the MEC server. In this scenario, we jointly optimize the offloading decisions, the time slots devoted to EH, information decoding, local computation/offloading and the offloading powers to minimize the total energy cost of the ULPDs. Numerical results illustrate the effectiveness of the proposed framework.