Intelligent Reflecting Surface Assisted Mobile Edge Computing for Internet of Things

Zheng Chu, Pei Xiao, Mohammad Shojafar, De Mi, Juquan Mao, Wanming Hao

Research output: Journal PublicationArticlepeer-review

80 Citations (Scopus)


This letter studies the impact of an intelligent reflecting surface (IRS) on computational performance in a mobile edge computing (MEC) system. Specifically, an access point (AP) equipped with an edge server provides MEC services to multiple Internet of Thing (IoT) devices that choose to offload a portion of their own computational tasks to the AP with the remaining portion being locally computed. We deploy an IRS to enhance the computational performance of the MEC system by intelligently adjusting the phase shift of each reflecting element. A joint design problem is formulated for the considered IRS assisted MEC system, aiming to optimize its sum computational bits and taking into account the CPU frequency, the offloading time allocation, transmit power of each device as well as the phase shifts of the IRS. To deal with the non-convexity of the formulated problem, we conduct our algorithm design by finding the optimized phase shifts first and then achieving the jointly optimal solution of the CPU frequency, the transmit power and the offloading time allocation by considering the Lagrange dual method and Karush-Kuhn-Tucker (KKT) conditions. Numerical evaluations highlight the advantage of the IRS-assisted MEC system in comparison with the benchmark schemes.

Original languageEnglish
Article number9270605
Pages (from-to)619-623
Number of pages5
JournalIEEE Wireless Communications Letters
Issue number3
Publication statusPublished - Mar 2021
Externally publishedYes


  • computational offloading
  • Intelligent reflecting surface (IRS)
  • local computing
  • mobile edge computing (MEC)
  • phase shifts

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering


Dive into the research topics of 'Intelligent Reflecting Surface Assisted Mobile Edge Computing for Internet of Things'. Together they form a unique fingerprint.

Cite this