TY - JOUR
T1 - Sub-Channel Scheduling, Task Assignment, and Power Allocation for OMA-Based and NOMA-Based MEC Systems
AU - Wang, Kaidi
AU - Fang, Fang
AU - Da Costa, Daniel Benevides
AU - Ding, Zhiguo
N1 - Funding Information:
Manuscript received June 17, 2020; revised October 21, 2020; accepted December 19, 2020. Date of publication December 25, 2020; date of current version April 16, 2021. The work of Z. Ding was supported by the UK Engineering and Physical Sciences Research Council (EPSRC) under Grant number EP/P009719/2. This article was presented in part at the 2019 IEEE Global Communication Conference (GOLBECOM), Waikoloa, HI, USA, December, 2019. The associate editor coordinating the review of this article and approving it for publication was F. Zhou. (Corresponding author: Kaidi Wang.) Kaidi Wang and Zhiguo Ding are with the Department of Electrical and Electronic Engineering, The University of Manchester, Manchester M13 9PL, U.K. (e-mail: [email protected]; [email protected]).
Publisher Copyright:
© 1972-2012 IEEE.
PY - 2021/4
Y1 - 2021/4
N2 - In this paper, sub-channel scheduling, task assignment and power allocation are investigated for orthogonal multiple access (OMA)-based and non-orthogonal multiple access (NOMA)-based mobile edge computing (MEC) systems. Based on different channel conditions and computational capacities, computational tasks are partially offloaded to the MEC server via OMA or NOMA protocols. In order to minimize the total energy consumption, an optimization problem under the task execution latency constraint is formulated and divided into two sub-problems. By utilizing matching theory, the formulated sub-channel allocation problem is solved by a proposed low-complexity algorithm, where the joint optimization of task assignment and power allocation is performed at each iteration. Based on the delay constraint, some insights are obtained, and the closed-form solutions of task assignment coefficients and transmit power are derived. Furthermore, the offloading strategy in both OMA and NOMA schemes is analyzed, which shows that the optimal task assignment coefficient is decided by the energy consumption efficiency (ECE). Simulation results indicate that: i) the proposed sub-channel allocation algorithm and derived closed-form solutions can significantly improve the MEC system in terms of the energy consumption; ii) the provided offloading strategy can be dynamically and efficiently employed with different channel conditions and computational capacities.
AB - In this paper, sub-channel scheduling, task assignment and power allocation are investigated for orthogonal multiple access (OMA)-based and non-orthogonal multiple access (NOMA)-based mobile edge computing (MEC) systems. Based on different channel conditions and computational capacities, computational tasks are partially offloaded to the MEC server via OMA or NOMA protocols. In order to minimize the total energy consumption, an optimization problem under the task execution latency constraint is formulated and divided into two sub-problems. By utilizing matching theory, the formulated sub-channel allocation problem is solved by a proposed low-complexity algorithm, where the joint optimization of task assignment and power allocation is performed at each iteration. Based on the delay constraint, some insights are obtained, and the closed-form solutions of task assignment coefficients and transmit power are derived. Furthermore, the offloading strategy in both OMA and NOMA schemes is analyzed, which shows that the optimal task assignment coefficient is decided by the energy consumption efficiency (ECE). Simulation results indicate that: i) the proposed sub-channel allocation algorithm and derived closed-form solutions can significantly improve the MEC system in terms of the energy consumption; ii) the provided offloading strategy can be dynamically and efficiently employed with different channel conditions and computational capacities.
KW - Mobile edge computing (MEC)
KW - non-orthogonal multiple access (NOMA)
KW - power allocation
KW - sub-channel scheduling
KW - task assignment
UR - https://www.scopus.com/pages/publications/85098784797
U2 - 10.1109/TCOMM.2020.3047440
DO - 10.1109/TCOMM.2020.3047440
M3 - Article
AN - SCOPUS:85098784797
SN - 0090-6778
VL - 69
SP - 2692
EP - 2708
JO - IEEE Transactions on Communications
JF - IEEE Transactions on Communications
IS - 4
M1 - 9308935
ER -