Resource Optimization for the Multi-user MIMO Systems Assisted Edge Cloud Computing

Resource Optimization for the Multi-user MIMO Systems Assisted Edge Cloud Computing

연구 분야: Networking

학회: 2021 IEEE 6th International Conference on Signal and Image Processing (ICSIP)

In this paper, MIMO is adopted to facilitate offloading in Mobile Edge Computing (MEC) systems which is superior to the traditional MEC systems without using MIMO scheme. Therefore, the high channel capacity and low latency of large-scale MIMO can be achieved to allow users to offload data to the MEC systems at the same time, thus greatly reducing the energy consumption and completion time during the data offloading process. Firstly, a novel problem is formulated in the MIMO MEC system, which aims to minimize the total energy consumption of the MEC system under the condition of satisfying the minimum delay constraint, including the energy consumption of the user local, the energy consumption of the uplink system, the energy consumption of the edge cloud and the energy consumption of the downlink system. Because of the complexity of the initial problem, the optimization problem is transformed into a delay assignment problem, and then, the initial problem is transformed into two sub-problems about the convex function. Finally, we propose an iterative algorithm named Nested Gradient Iterative Algorithm (NGIA) to solve the decoupled problem, which is composed of external gradient iteration and internal gradient iteration. Meanwhile, the superiority of the proposed algorithm is demonstrated by the simulation results in reducing the total energy consumption of the MEC system.