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Resource allocation for NOMA MEC offloading

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Resource allocation for NOMA MEC offloading. / Zhu, J.; Wang, J.; Huang, Y.; Fang, F.; Navaie, K.; DIng, Z.

2019 IEEE Global Communications Conference (GLOBECOM). IEEE, 2020. (IEEE Global Communications Conference (GLOBECOM); Vol. 2019).

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paperpeer-review

Harvard

Zhu, J, Wang, J, Huang, Y, Fang, F, Navaie, K & DIng, Z 2020, Resource allocation for NOMA MEC offloading. in 2019 IEEE Global Communications Conference (GLOBECOM). IEEE Global Communications Conference (GLOBECOM), vol. 2019, IEEE. https://doi.org/10.1109/TWC.2020.2988532, https://doi.org/10.1109/GLOBECOM38437.2019.9013239

APA

Zhu, J., Wang, J., Huang, Y., Fang, F., Navaie, K., & DIng, Z. (2020). Resource allocation for NOMA MEC offloading. In 2019 IEEE Global Communications Conference (GLOBECOM) (IEEE Global Communications Conference (GLOBECOM); Vol. 2019). IEEE. https://doi.org/10.1109/TWC.2020.2988532, https://doi.org/10.1109/GLOBECOM38437.2019.9013239

Vancouver

Zhu J, Wang J, Huang Y, Fang F, Navaie K, DIng Z. Resource allocation for NOMA MEC offloading. In 2019 IEEE Global Communications Conference (GLOBECOM). IEEE. 2020. (IEEE Global Communications Conference (GLOBECOM)). https://doi.org/10.1109/TWC.2020.2988532, https://doi.org/10.1109/GLOBECOM38437.2019.9013239

Author

Zhu, J. ; Wang, J. ; Huang, Y. ; Fang, F. ; Navaie, K. ; DIng, Z. / Resource allocation for NOMA MEC offloading. 2019 IEEE Global Communications Conference (GLOBECOM). IEEE, 2020. (IEEE Global Communications Conference (GLOBECOM)).

Bibtex

@inproceedings{de3914e821204492a07b33eceb1267e6,
title = "Resource allocation for NOMA MEC offloading",
abstract = "In this paper, we consider a nonorthogonal multiple access (NOMA) assisted mobile edge computing (MEC) system where the power and time are jointly optimized to reduce the energy consumption and delay. In order to achieve a tradeoff between energy consumption and delay, we introduce weighting factors, and the optimization problem is formulated to minimize the weighted sum of energy consumption and delay. In the literature, only two offloading strategies, i. e., orthogonal multiple access (OMA) and pure NOMA, are mainly considered. In this paper, we investigate a third strategy, hybrid NOMA, which contains the strategies of OMA and pure NOMA. As the main contribution, we analytically characterize the optimal resource allocation, i. e., the joint power and time allocation, for two-scheduled-user case. Simulation results show that the proposed resource allocation method in hybrid NOMA systems yields lower energy consumption and delay than the conventional OMA scheme. ",
keywords = "Energy consumption, Mobile edge computing, Non-orthogonal multiple access, Resource allocation, Time delay, Edge computing, Energy utilization, Lower energies, Multiple access, Non-orthogonal, Optimal resource allocation, Optimization problems, Time allocation, Weighted Sum, Weighting factors, Green computing",
author = "J. Zhu and J. Wang and Y. Huang and F. Fang and K. Navaie and Z. DIng",
year = "2020",
month = feb,
day = "27",
doi = "10.1109/TWC.2020.2988532",
language = "English",
isbn = "9781728109633",
series = "IEEE Global Communications Conference (GLOBECOM)",
publisher = "IEEE",
booktitle = "2019 IEEE Global Communications Conference (GLOBECOM)",

}

RIS

TY - GEN

T1 - Resource allocation for NOMA MEC offloading

AU - Zhu, J.

AU - Wang, J.

AU - Huang, Y.

AU - Fang, F.

AU - Navaie, K.

AU - DIng, Z.

PY - 2020/2/27

Y1 - 2020/2/27

N2 - In this paper, we consider a nonorthogonal multiple access (NOMA) assisted mobile edge computing (MEC) system where the power and time are jointly optimized to reduce the energy consumption and delay. In order to achieve a tradeoff between energy consumption and delay, we introduce weighting factors, and the optimization problem is formulated to minimize the weighted sum of energy consumption and delay. In the literature, only two offloading strategies, i. e., orthogonal multiple access (OMA) and pure NOMA, are mainly considered. In this paper, we investigate a third strategy, hybrid NOMA, which contains the strategies of OMA and pure NOMA. As the main contribution, we analytically characterize the optimal resource allocation, i. e., the joint power and time allocation, for two-scheduled-user case. Simulation results show that the proposed resource allocation method in hybrid NOMA systems yields lower energy consumption and delay than the conventional OMA scheme.

AB - In this paper, we consider a nonorthogonal multiple access (NOMA) assisted mobile edge computing (MEC) system where the power and time are jointly optimized to reduce the energy consumption and delay. In order to achieve a tradeoff between energy consumption and delay, we introduce weighting factors, and the optimization problem is formulated to minimize the weighted sum of energy consumption and delay. In the literature, only two offloading strategies, i. e., orthogonal multiple access (OMA) and pure NOMA, are mainly considered. In this paper, we investigate a third strategy, hybrid NOMA, which contains the strategies of OMA and pure NOMA. As the main contribution, we analytically characterize the optimal resource allocation, i. e., the joint power and time allocation, for two-scheduled-user case. Simulation results show that the proposed resource allocation method in hybrid NOMA systems yields lower energy consumption and delay than the conventional OMA scheme.

KW - Energy consumption

KW - Mobile edge computing

KW - Non-orthogonal multiple access

KW - Resource allocation

KW - Time delay

KW - Edge computing

KW - Energy utilization

KW - Lower energies

KW - Multiple access

KW - Non-orthogonal

KW - Optimal resource allocation

KW - Optimization problems

KW - Time allocation

KW - Weighted Sum

KW - Weighting factors

KW - Green computing

U2 - 10.1109/TWC.2020.2988532

DO - 10.1109/TWC.2020.2988532

M3 - Conference contribution/Paper

SN - 9781728109633

T3 - IEEE Global Communications Conference (GLOBECOM)

BT - 2019 IEEE Global Communications Conference (GLOBECOM)

PB - IEEE

ER -