Joint Power Allocation and Task Offloading in NOMA Enhanced MEC for ABS-Assisted ITS
Pengcheng Qian, Liang Wang, Yaguang Lin, Jiarong Du, Xiuxiu Dong
Abstract
In the traditional ITS, the road side unit (RSU) is used as the edge server to provide computing services for connected and autonomous vehicles (CAVs). However, the rapid growth of on-board devices creates a strain on communication resources. Thus, in this letter we investigate the application of non-orthogonal multiple access (NOMA) and mobile edge computing (MEC) in air base station (ABS)-assisted ITS. In this scenario, CAVs can partially offload tasks to RSUs and ABS simultaneously through NOMA. To further reduce total system delay, ABS can guide heavy loaded RSU to migrate tasks to achieve load balancing. We jointly optimize the transmission power and offloading decision, and model CAVs’ task processing delay minimization problem as a mixed integer nonlinear problem. To solve this problem, we propose a two-step strategy. First, we obtain the optimal transmission power and task division ratio through the proposed optimal pre-offloading decision (OPD) algorithm, and then determine the offloading object through the devised subtask migration (STM) algorithm. Simulation results verify the advantages of our proposed scheme.