TY - GEN
T1 - Energy-Efficient Multi-User Mobile-Edge Computation Offloading in Massive MIMO Enabled HetNets
AU - Hao, Yuanyuan
AU - Ni, Qiang
AU - Li, Hai
AU - Hou, Shujuan
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/5
Y1 - 2019/5
N2 - In this paper, we investigate the energy-efficient multi-user mobile-edge computing offloading problem in massive MIMO enabled HetNets, where the CPU-cycle frequency of mobile devices, uplink power control, computational task offloading ratio and uplink transmission duration are jointly optimized. The problem is formulated as minimizing the energy consumption of all mobile devices while satisfying the maximum latency requirement. Specifically, to address this non-convex problem, a low-complexity algorithm is proposed relied on alternating optimization, where we address the joint computational task offloading ratio and uplink transmission duration optimization problem and the uplink power control problem iteratively. Besides, the effectiveness and convergence of the proposed iterative algorithm are analytically studied. Numerical results demonstrate that our proposed algorithm consumes less energy compared to local computing and full uploading schemes, and the application of massive MIMO in HetNets helps to reduce energy consumption of mobile devices.
AB - In this paper, we investigate the energy-efficient multi-user mobile-edge computing offloading problem in massive MIMO enabled HetNets, where the CPU-cycle frequency of mobile devices, uplink power control, computational task offloading ratio and uplink transmission duration are jointly optimized. The problem is formulated as minimizing the energy consumption of all mobile devices while satisfying the maximum latency requirement. Specifically, to address this non-convex problem, a low-complexity algorithm is proposed relied on alternating optimization, where we address the joint computational task offloading ratio and uplink transmission duration optimization problem and the uplink power control problem iteratively. Besides, the effectiveness and convergence of the proposed iterative algorithm are analytically studied. Numerical results demonstrate that our proposed algorithm consumes less energy compared to local computing and full uploading schemes, and the application of massive MIMO in HetNets helps to reduce energy consumption of mobile devices.
UR - http://www.scopus.com/inward/record.url?scp=85070223122&partnerID=8YFLogxK
U2 - 10.1109/ICC.2019.8761356
DO - 10.1109/ICC.2019.8761356
M3 - Conference contribution
AN - SCOPUS:85070223122
T3 - IEEE International Conference on Communications
BT - 2019 IEEE International Conference on Communications, ICC 2019 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2019 IEEE International Conference on Communications, ICC 2019
Y2 - 20 May 2019 through 24 May 2019
ER -
