Presenter Information

Qun Wang, Utah State University

Class

Article

College

College of Engineering

Department

Electrical and Computer Engineering Department

Faculty Mentor

Rose Qingyang Hu

Presentation Type

Oral Presentation

Abstract

Ultra-dense Internet of Things (IoT) network has greatly facilitated the development of smart environments and the realization of diverse sophisticated applications. Power constrained and resource-limited IoT devices often need to perform computation-intensive and delay-sensitive tasks in such a network. Mobile edge computing and non-orthogonal multiple access are two promising techniques to address the corresponding challenges. In order to improve the fairness and resource efficiency among IoT users, resource allocation problems are formulated in ultra-dense MEC-enabled IoT networks with NOMA considered. An iterative algorithm based on successive convex approximation technique is proposed to solve those challenging non-convex problems.

Location

Room 204

Start Date

4-11-2019 12:00 PM

End Date

4-11-2019 1:15 PM

Included in

Engineering Commons

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Apr 11th, 12:00 PM Apr 11th, 1:15 PM

Fair Resource Allocation in an MEC-Enabled Ultra-Dense IoT Network with NOMA

Room 204

Ultra-dense Internet of Things (IoT) network has greatly facilitated the development of smart environments and the realization of diverse sophisticated applications. Power constrained and resource-limited IoT devices often need to perform computation-intensive and delay-sensitive tasks in such a network. Mobile edge computing and non-orthogonal multiple access are two promising techniques to address the corresponding challenges. In order to improve the fairness and resource efficiency among IoT users, resource allocation problems are formulated in ultra-dense MEC-enabled IoT networks with NOMA considered. An iterative algorithm based on successive convex approximation technique is proposed to solve those challenging non-convex problems.