TY - JOUR
T1 - Optimal Offloading with Non-Orthogonal Multiple Access in Mobile Edge Computing
AU - Gu, Qi
AU - Wang, Gongpu
AU - Liu, Jingxian
AU - Fan, Rongfei
AU - Fan, Dian
AU - Zhong, Zhangdui
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018
Y1 - 2018
N2 - By allowing mobile device to offload all or part of a latency-constrained computational task to a base station at the edge of a network, mobile edge computing (MEC) is a promising technique to help the mobile device save its energy consumption. In this paper, we consider the scenario with one mobile device and multiple edge base stations, which is usual in practice. Nonorthogonal multiple access (NOMA) technique is implemented. An optimization problem is formulated, in which the transmission power to every edge base station and the amount of data to be offloaded for computation is optimized to minimize the total energy consumption of the mobile device. However, the formulated optimization problem is non-convex. To get the global optimal solution, we decompose the formulated optimization problem into two levels. In the lower level, a convex optimization problem is required to be solved. By finding out some special property of the lower level optimization problem, the upper level optimization problem can be formulated as a monotonic optimization problem, whose global optimal solution is achievable. Numerical results verify the effectiveness of our proposed method.
AB - By allowing mobile device to offload all or part of a latency-constrained computational task to a base station at the edge of a network, mobile edge computing (MEC) is a promising technique to help the mobile device save its energy consumption. In this paper, we consider the scenario with one mobile device and multiple edge base stations, which is usual in practice. Nonorthogonal multiple access (NOMA) technique is implemented. An optimization problem is formulated, in which the transmission power to every edge base station and the amount of data to be offloaded for computation is optimized to minimize the total energy consumption of the mobile device. However, the formulated optimization problem is non-convex. To get the global optimal solution, we decompose the formulated optimization problem into two levels. In the lower level, a convex optimization problem is required to be solved. By finding out some special property of the lower level optimization problem, the upper level optimization problem can be formulated as a monotonic optimization problem, whose global optimal solution is achievable. Numerical results verify the effectiveness of our proposed method.
KW - Mobile edge computing (MEC)
KW - non-orthogonal multiple access (NOMA)
KW - optimal offloading
UR - http://www.scopus.com/inward/record.url?scp=85063513364&partnerID=8YFLogxK
U2 - 10.1109/GLOCOM.2018.8647179
DO - 10.1109/GLOCOM.2018.8647179
M3 - Conference article
AN - SCOPUS:85063513364
SN - 2334-0983
JO - Proceedings - IEEE Global Communications Conference, GLOBECOM
JF - Proceedings - IEEE Global Communications Conference, GLOBECOM
M1 - 8647179
T2 - 2018 IEEE Global Communications Conference, GLOBECOM 2018
Y2 - 9 December 2018 through 13 December 2018
ER -