Joint Access and Resource Allocation in Ultradense mmWave NOMA Networks With Mobile Edge Computing

This article considers a two-tier heterogeneous network consisting of conventional sub-6-GHz macrocells along with millimeter-wave (mmWave) small cells, where mobile devices (MDs) can connect to either macrocell or small cells opportunistically via the nonorthogonal multiple access (NOMA) protocol....

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Published inIEEE internet of things journal Vol. 7; no. 2; pp. 1531 - 1547
Main Authors Nouri, Nima, Abouei, Jamshid, Jaseemuddin, Muhammad, Anpalagan, Alagan
Format Journal Article
LanguageEnglish
Published Piscataway IEEE 01.02.2020
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Algorithms
Computation offloading
Decision analysis
Delay
Delays
Edge computing
Electronic devices
Energy consumption
Internet of Things
Internet of Things (IoT) networks
IoT
Iterative algorithms
Iterative methods
Millimeter waves
millimeter-wave (mmWave)
Mobile computing
mobile edge computing
Nonorthogonal multiple access
nonorthogonal multiple access (NOMA) technique
Optimization
Queues
Queuing theory
Resource allocation
Resource management
Servers
successive convex approximation (SCA)
Task analysis
ultradense (UD)
Wireless networks
Online AccessGet full text
ISSN2327-4662
2327-4662
DOI10.1109/JIOT.2019.2956409

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Abstract This article considers a two-tier heterogeneous network consisting of conventional sub-6-GHz macrocells along with millimeter-wave (mmWave) small cells, where mobile devices (MDs) can connect to either macrocell or small cells opportunistically via the nonorthogonal multiple access (NOMA) protocol. We employ the queuing theory in our network model to conduct an assessment on the execution delay, energy consumption and the total cost of offloading tasks in a mobile-edge computation offloading (MECO) system. The main goal is to design an energy-efficient MECO decision algorithm in an ultradense Internet of Thing (UD-IoT) network to analyze the tradeoff between execution delay and energy consumption. The proposed scheme jointly optimizes the communication and computation resource management, subject to the energy and delay constraints. Due to the mixed-integer nonlinear problem (MINLP) for resource allocation and computation offloading, an iterative algorithm along with the successive convex approximation (SCA) is proposed to achieve the optimum local frequency scheduling, power allocation, and computation offloading. The superior performance of the proposed MECO algorithm in our UD-IoT network is verified by the extensive numerical results.
AbstractList This article considers a two-tier heterogeneous network consisting of conventional sub-6-GHz macrocells along with millimeter-wave (mmWave) small cells, where mobile devices (MDs) can connect to either macrocell or small cells opportunistically via the nonorthogonal multiple access (NOMA) protocol. We employ the queuing theory in our network model to conduct an assessment on the execution delay, energy consumption and the total cost of offloading tasks in a mobile-edge computation offloading (MECO) system. The main goal is to design an energy-efficient MECO decision algorithm in an ultradense Internet of Thing (UD-IoT) network to analyze the tradeoff between execution delay and energy consumption. The proposed scheme jointly optimizes the communication and computation resource management, subject to the energy and delay constraints. Due to the mixed-integer nonlinear problem (MINLP) for resource allocation and computation offloading, an iterative algorithm along with the successive convex approximation (SCA) is proposed to achieve the optimum local frequency scheduling, power allocation, and computation offloading. The superior performance of the proposed MECO algorithm in our UD-IoT network is verified by the extensive numerical results.
Author Nouri, Nima
Anpalagan, Alagan
Abouei, Jamshid
Jaseemuddin, Muhammad
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Snippet This article considers a two-tier heterogeneous network consisting of conventional sub-6-GHz macrocells along with millimeter-wave (mmWave) small cells, where...
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SubjectTerms Algorithms
Computation offloading
Decision analysis
Delay
Delays
Edge computing
Electronic devices
Energy consumption
Internet of Things
Internet of Things (IoT) networks
IoT
Iterative algorithms
Iterative methods
Millimeter waves
millimeter-wave (mmWave)
Mobile computing
mobile edge computing
Nonorthogonal multiple access
nonorthogonal multiple access (NOMA) technique
Optimization
Queues
Queuing theory
Resource allocation
Resource management
Servers
successive convex approximation (SCA)
Task analysis
ultradense (UD)
Wireless networks
Title Joint Access and Resource Allocation in Ultradense mmWave NOMA Networks With Mobile Edge Computing
URI https://ieeexplore.ieee.org/document/8915829
https://www.proquest.com/docview/2357209459
Volume 7
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