Network Slicing for NOMA-Enabled Edge Computing

The 5G network presents a new horizon with tremendous opportunities for future generation wireless networks. Mobile edge computing (MEC), non-orthogonal multiple access (NOMA), and network slicing (NS) are some of the key enablers for 5G. MEC reduces the latency to a great extent for a wireless netw...

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Vydané v:IEEE transactions on cloud computing Ročník 11; číslo 1; s. 811 - 821
Hlavní autori: Hossain, Mohammad Arif, Ansari, Nirwan
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Piscataway IEEE 01.01.2023
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:
5G mobile communication
Algorithms
Completion time
Computational modeling
Edge computing
Energy consumption
energy efficiency
Heuristic methods
Mobile computing
Mobile edge computing
Network latency
Network slicing
NOMA
Nonorthogonal multiple access
Optimization
Quality of service architectures
Resource management
spectral efficiency
Task analysis
Uplink
uplink energy consumption minimization
Wireless networks
ISSN:2168-7161, 2372-0018
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Shrnutí:The 5G network presents a new horizon with tremendous opportunities for future generation wireless networks. Mobile edge computing (MEC), non-orthogonal multiple access (NOMA), and network slicing (NS) are some of the key enablers for 5G. MEC reduces the latency to a great extent for a wireless network, while NOMA gives access to more users with resource constraints. NS provides users with a better quality of service and network operators with more flexibility. In this work, we propose an NS technique enabled with NOMA for a MEC network. The proposed NS technique improves service latency for MEC users and reduces unnecessary allocation of radio resources in NOMA. The saved resources can be leveraged to accommodate more users, thus increasing the spectral efficiency of the network. We consider different types of services based on the task completion time of users in this work. The primary focus is to optimize the total energy consumption for wireless uplink transmission for the NOMA-enabled sliced MEC network. We also propose a heuristic algorithm as an alternative to reduce the time and computational complexities of the optimization algorithm and simulate the results extensively to show the effectiveness of our proposed algorithm.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:2168-7161
2372-0018
DOI:10.1109/TCC.2021.3117754