V. Kumar, M. F. Hanif, M. Juntti and L. -N. Tran, "A Max-Min Task Offloading Algorithm for Mobile Edge Computing Using Non-Orthogonal Multiple Access," in IEEE Transactions on Vehicular Technology, vol. 72, no. 9, pp. 12332-12337, Sept. 2023, doi: 10.1109/TVT.2023.3263791.
A max-min task offloading algorithm for mobile edge computing using non-orthogonal multiple access
|Author:||Kumar, Vaibhav1; Hanif, Muhammad Fainan2; Juntti, Markku3;|
1School of Electrical and Electronic Engineering, University College Dublin, Dublin, Ireland
2Institute of Electrical, Electronics and Computer Engineering, University of the Punjab, Lahore, Pakistan
3Centre for Wireless Communications, University of Oulu, Oulu, Finland
|Online Access:||PDF Full Text (PDF, 1 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe20230912123502
Institute of Electrical and Electronics Engineers,
|Publish Date:|| 2023-09-12
To mitigate the computational power gap between the network core and edges, mobile edge computing (MEC) is poised to play a fundamental role in future generations of wireless networks. In this correspondence, we consider a non-orthogonal multiple access (NOMA) transmission model to maximize the worst task to be offloaded among all users to the network edge server. A provably convergent and efficient algorithm is developed to solve the considered non-convex optimization problem for maximizing the minimum number of offloaded bits in a multi-user NOMA-MEC system. Compared to the approach of optimized orthogonal multiple access (OMA), for given MEC delay, power and energy limits, the NOMA-based system considerably outperforms its OMA-based counterpart in MEC settings. Numerical results demonstrate that the proposed algorithm for NOMA-based MEC is particularly useful for delay sensitive applications.
IEEE transactions on vehicular technology
|Pages:||12332 - 12337|
|Type of Publication:||
A1 Journal article – refereed
|Field of Science:||
213 Electronic, automation and communications engineering, electronics
Academy of Finland under 6G Flagship (Grant Number: 346208)
|Academy of Finland Grant Number:||
346208 (Academy of Finland Funding decision)
This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/.