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Delay Minimization for Massive MIMO Assisted Mobile Edge Computing
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DOI：10.1109/TVT.2020.2979434.png)
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Abstract
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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.
Keywords:
Delays
MIMO communication
Resource management
Minimization
Energy consumption
Task analysis
Wireless communication
Massive multiple-input multiple-output (MIMO)
mobile edge computing (MEC)
delay minimization
joint resource allocation
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