Learning Driven NOMA Assisted Vehicular Edge Computing via Underlay Spectrum Sharing

Edge computing has been considered as one of the key paradigms in the fifth-generation (5G) networks for enabling computation-intensive yet latency-sensitive vehicular Internet services. In this paper, we investigate non-orthogonal multiple access (NOMA) assisted vehicular edge computing via underla...

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Vydáno v:	IEEE transactions on vehicular technology Ročník 70; číslo 1; s. 977 - 992
Hlavní autoři:	Qian, Liping, Wu, Yuan, Yu, Ningning, Jiang, Fuli, Zhou, Haibo, Quek, Tony Q.S.
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New York IEEE 01.01.2021 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:	Algorithms Cochannel interference Combinatorial analysis Computation offloading Computational modeling Convexity Copper Delay Delays Edge computing Entropy (Information theory) Frequency division multiple access Machine learning Network latency NOMA Non-orthogonal multiple access Nonorthogonal multiple access Optimization Resource management Reuse Servers spectrum sharing stochastic learning vehicular edge computing
ISSN:	0018-9545, 1939-9359
On-line přístup:	Získat plný text
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