TY - JOUR
T1 - Energy-Efficient Resource Allocation for NOMA-MEC Networks with Imperfect CSI
AU - Fang, Fang
AU - Wang, Kaidi
AU - Ding, Zhiguo
AU - Leung, Victor C.M.
N1 - Funding Information:
Manuscript received September 12, 2020; revised November 22, 2020 and December 29, 2020; accepted February 1, 2021. Date of publication February 12, 2021; date of current version May 18, 2021. The work of Z. Ding was supported by the UK Engineering and Physical Sciences Research Council (EPSRC) under grant number EP/P009719/2. The work of V.C.M. Leung was supported by the Guangdong “Pearl River Talent Recruitment Program” under grant number 2019ZT08 × 603, and by the Canadian Natural Sciences and Engineering Research Council. 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 - 2021/5
Y1 - 2021/5
N2 - The combination of non-orthogonal multiple access (NOMA) and multi-access edge computing (MEC) can significantly improve the system performance including communication coverage, spectrum efficiency, etc. In this article, we focus on energy-efficient resource allocation for a multi-user multi-BS NOMA-MEC network with imperfect channel state information (CSI), where each user can upload its tasks to multiple base stations (BSs) for remote executions. We propose an optimization scheme, including task assignment, power allocation and user association, to minimize energy consumption. Specifically, we transform the probabilistic problem into a non-probabilistic one. To efficiently solve this nonconvex energy minimization problem, we first investigate the one-user two-BS case and derive the optimal closed-form expressions of task assignment and power allocation via the bilevel programming method. Subsequently, based on the derived optimal solution, we propose a low complexity algorithm for the user association in the multi-user multi-BS scenario. Simulations demonstrate that the proposed algorithm can yield much better performance than the conventional OMA scheme and the identical results with lower complexity from the exhaustive search with the small number of BSs.
AB - The combination of non-orthogonal multiple access (NOMA) and multi-access edge computing (MEC) can significantly improve the system performance including communication coverage, spectrum efficiency, etc. In this article, we focus on energy-efficient resource allocation for a multi-user multi-BS NOMA-MEC network with imperfect channel state information (CSI), where each user can upload its tasks to multiple base stations (BSs) for remote executions. We propose an optimization scheme, including task assignment, power allocation and user association, to minimize energy consumption. Specifically, we transform the probabilistic problem into a non-probabilistic one. To efficiently solve this nonconvex energy minimization problem, we first investigate the one-user two-BS case and derive the optimal closed-form expressions of task assignment and power allocation via the bilevel programming method. Subsequently, based on the derived optimal solution, we propose a low complexity algorithm for the user association in the multi-user multi-BS scenario. Simulations demonstrate that the proposed algorithm can yield much better performance than the conventional OMA scheme and the identical results with lower complexity from the exhaustive search with the small number of BSs.
KW - Energy-efficient
KW - imperfect channel state information (CSI)
KW - multi-access edge computing (MEC)
KW - non-orthogonal multiple access (NOMA)
KW - resource allocation
UR - http://www.scopus.com/inward/record.url?scp=85100834776&partnerID=8YFLogxK
U2 - 10.1109/TCOMM.2021.3058964
DO - 10.1109/TCOMM.2021.3058964
M3 - Article
AN - SCOPUS:85100834776
SN - 0090-6778
VL - 69
SP - 3436
EP - 3449
JO - IEEE Transactions on Communications
JF - IEEE Transactions on Communications
IS - 5
M1 - 9353556
ER -