Open AccessResearch on Transmission and Offloading Scheme of MEC-IRS for Distribution Network Service
Author(s) -
Bingsen Xia,
Yuanchun Tang
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/2087/1/012074
Subject(s) - computer science , mobile edge computing , computer network , node (physics) , reinforcement learning , the internet , transmission (telecommunications) , service (business) , task (project management) , internet of things , enhanced data rates for gsm evolution , distributed computing , edge computing , base station , telecommunications , server , engineering , embedded system , artificial intelligence , economy , structural engineering , world wide web , economics , systems engineering
the paper introduces IRS to assist offloading, and the propagation Environment can be intelligently changed by changing the reflection unit of the IRS, This article proposes an IRS-assisted MEC power distribution Internet of Things system, and studies the gain effect of IRS in the MEC system. In this system, the single antenna equipment can choose to unload a small part of its computing task to the edge computing node of the distribution Internet of things through the multi antenna access point with the help of IRS. In this paper, the delay minimization problem of the whole system is established, the DNQ reinforcement learning algorithm is used to solve the problem, which can effectively change the coverage of smart substations.