4.7 Article

D2D Communications Meet Mobile Edge Computing for Enhanced Computation Capacity in Cellular Networks

期刊

IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS
卷 18, 期 3, 页码 1750-1763

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TWC.2019.2896999

关键词

Mobile edge computing; device-to-device communications; computation capacity; task offloading; resource allocation; cellular networks

资金

  1. Natural Science Foundation of China [61671407, 61831004]
  2. Open Research Fund of the State Key Laboratory of Integrated Services Networks, Xidian University [ISN18-13]
  3. Zhejiang Provincial Natural Science Foundation for Distinguished Young Scholars [LR19F010002]
  4. Fundamental Research Funds for the Central Universities

向作者/读者索取更多资源

The future 5G wireless networks aim to support high-rate data communications and high-speed mobile computing. To achieve this goal, the mobile edge computing (MEC) and device-to-device (D2D) communications have been recently developed, both of which take advantage of the proximity for better performance. In this paper, we integrate the D2D communications with MEC to further improve the computation capacity of the cellular networks, where the task of each device can be offloaded to an edge node and a nearby D2D device. We aim to maximize the number of devices supported by the cellular networks with the constraints of both communication and computation resources. The optimization problem is formulated as a mixed integer non-linear problem, which is not easy to solve in general. To tackle it, we decouple it into two subproblems. The first one minimizes the required edge computation resource for a given D2D pair, while the second one maximizes the number of supported devices via optimal D2D pairing. We prove that the optimal solutions to the two subproblems compose the optimal solution to the original problem. Then, the optimal algorithm to the original problem is developed by solving two subproblems, and some insightful results, such as the optimal transmit power allocation and the task offloading strategy, are also highlighted. Our proposal is finally tested by extensive numerical simulation results, which demonstrate that combining D2D communications with MEC can significantly enhance the computation capacity of the system.

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