Delay minimization for massive MIMO assisted mobile edge computing

Ming Zeng, Wanming Hao, Octavia A. Dobre, H. Vincent Poor

Research output: Contribution to journalArticlepeer-review

32 Scopus citations

Abstract

Mobile edge computing (MEC) has been envisioned as a promising technology for enhancing the computational capacities of mobile devices, by enabling computational task offloading. In this article, we employ massive multiple-input multiple-output methods to facilitate offloading in MEC. Our objective is to minimize the maximum delay for offloading and computing among the users, which requires a joint allocation of wireless and computational resources. Both perfect and imperfect channel state information (CSI) are considered. Under perfect CSI, we derive a semi-closed-form solution for the formulated problem. Under imperfect CSI, since the formulated problem is non-convex, we transform it into a convex one using a successive convex approximation technique and propose an iterative algorithm to solve it. Presented numerical results show the benefits of having a large number of antennas at the base station, and the necessity of performing joint radio and computational resource allocation.

Original languageEnglish (US)
Article number9027954
Pages (from-to)6788-6792
Number of pages5
JournalIEEE Transactions on Vehicular Technology
Volume69
Issue number6
DOIs
StatePublished - Jun 2020

All Science Journal Classification (ASJC) codes

  • Aerospace Engineering
  • Electrical and Electronic Engineering
  • Computer Networks and Communications
  • Automotive Engineering

Keywords

  • Massive multiple-input multiple-output (MIMO)
  • delay minimization
  • joint resource allocation
  • mobile edge computing (MEC)

Fingerprint

Dive into the research topics of 'Delay minimization for massive MIMO assisted mobile edge computing'. Together they form a unique fingerprint.

Cite this