TY - JOUR
T1 - Optimal Resource Allocation for Delay Minimization in NOMA-MEC Networks
AU - Fang, Fang
AU - Xu, Yanqing
AU - Ding, Zhiguo
AU - Shen, Chao
AU - Peng, Mugen
AU - Karagiannidis, George K.
N1 - Funding Information:
Manuscript received January 17, 2020; revised May 29, 2020 and July 15, 2020; accepted August 18, 2020. Date of publication August 28, 2020; date of current version December 16, 2020. The work of M. Peng was supported by the National Natural Science Foundation of China under No. 61921003 and 61831002, and the Beijing Natural Science Foundation under No. JQ18016. The work of C. Shen was supported in part by the NSFC, China, under Grant 61871027 and Grant U1834210, in part by the State Key Laboratory of Rail Traffic Control and Safety under Grant RCS2019ZZ002. This article was presented in part at the 2019 IEEE Global Communications Conference, Waikoloa, HI, USA. The associate editor coordinating the review of this article and approving it for publication was M. A. A. Imran. (Corresponding author: Fang Fang.) Fang Fang is with the Department of Engineering, Durham University, Durham DH1 3LE, U.K. (e-mail: [email protected]).
Publisher Copyright:
© 1972-2012 IEEE.
PY - 2020/12
Y1 - 2020/12
N2 - Multi-access edge computing (MEC) can enhance the computing capability of mobile devices, while non-orthogonal multiple access (NOMA) can provide high data rates. Combining these two strategies can effectively benefit the network with spectrum and energy efficiency. In this paper, we investigate the task delay minimization in multi-user NOMA-MEC networks, where multiple users can offload their tasks simultaneously through the same frequency band. We adopt the partial offloading policy, in which each user can partition its computation task into offloading and locally computing parts. We aim to minimize the task delay among users by optimizing their tasks partition ratios and offloading transmit power. The delay minimization problem is first formulated, and it is shown that it is a nonconvex one. By carefully investigating its structure, we transform the original problem into an equivalent quasi-convex. In this way, a bisection search iterative algorithm is proposed in order to achieve the minimum task delay. To reduce the complexity of the proposed algorithm and evaluate its optimality, we further derive closed-form expressions for the optimal task partition ratio and offloading power for the case of two-user NOMA-MEC networks. Simulations demonstrate the convergence and optimality of the proposed algorithm and the effectiveness of the closed-form analysis.
AB - Multi-access edge computing (MEC) can enhance the computing capability of mobile devices, while non-orthogonal multiple access (NOMA) can provide high data rates. Combining these two strategies can effectively benefit the network with spectrum and energy efficiency. In this paper, we investigate the task delay minimization in multi-user NOMA-MEC networks, where multiple users can offload their tasks simultaneously through the same frequency band. We adopt the partial offloading policy, in which each user can partition its computation task into offloading and locally computing parts. We aim to minimize the task delay among users by optimizing their tasks partition ratios and offloading transmit power. The delay minimization problem is first formulated, and it is shown that it is a nonconvex one. By carefully investigating its structure, we transform the original problem into an equivalent quasi-convex. In this way, a bisection search iterative algorithm is proposed in order to achieve the minimum task delay. To reduce the complexity of the proposed algorithm and evaluate its optimality, we further derive closed-form expressions for the optimal task partition ratio and offloading power for the case of two-user NOMA-MEC networks. Simulations demonstrate the convergence and optimality of the proposed algorithm and the effectiveness of the closed-form analysis.
KW - Delay minimization
KW - multi-access edge computing (MEC)
KW - non-orthogonal multiple access (NOMA)
UR - http://www.scopus.com/inward/record.url?scp=85097983816&partnerID=8YFLogxK
U2 - 10.1109/TCOMM.2020.3020068
DO - 10.1109/TCOMM.2020.3020068
M3 - Article
AN - SCOPUS:85097983816
SN - 0090-6778
VL - 68
SP - 7867
EP - 7881
JO - IEEE Transactions on Communications
JF - IEEE Transactions on Communications
IS - 12
M1 - 9179779
ER -