Computation Efficiency Maximization for Wireless-Powered Mobile Edge Computing

Fuhui Zhou, Haijian Sun, Zheng Chu, Rose Qingyang Hu

Research output: Journal PublicationConference articlepeer-review

21 Citations (Scopus)


Energy-efficient computation is an inevitable trend for mobile edge computing (MEC) networks. However, resource allocation strategies for maximizing the computation efficiency have not been fully investigated. In this paper a computation efficiency maximization problem is formulated in the wireless-powered MEC network under a practical non-linear energy harvesting model. The energy harvesting time, the local computing frequency, the offtoading time, and power are all jointly optimized to maximize the computation efficiency under the max-min fairness criterion. The problem is non-convex and challenging to solve. An iterative algorithm is proposed to solve this problem. Simulation results show that our proposed resource allocation scheme outperforms the benchmark schemes in terms of the computation efficiency and verify the efficiency of our proposed algorithm. A tradeoff is elucidated between the achievable computation efficiency and the computation bits.

Original languageEnglish
Article number8647509
JournalProceedings - IEEE Global Communications Conference, GLOBECOM
Publication statusPublished - 2018
Externally publishedYes
Event2018 IEEE Global Communications Conference, GLOBECOM 2018 - Abu Dhabi, United Arab Emirates
Duration: 9 Dec 201813 Dec 2018


  • Computation efficiency
  • edge computing
  • fairness
  • non-linear energy harvesting model
  • resource allocation

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Hardware and Architecture
  • Signal Processing


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