TY - JOUR
T1 - Computation Efficiency Optimization for Millimeter-Wave Mobile Edge Computing Networks with NOMA
AU - Yu, Xiangbin
AU - Xu, Fangcheng
AU - Cai, Jiali
AU - Dang, Xiao-yu
AU - Wang, Kezhi
N1 - Funding information: This work is supported in part by National Natural Science Foundation of China (61971220, 62031017, 61971221), and Open Research Fund of State Key Laboratory of Millimeter Waves of Southeast University (K202215).
PY - 2023/8/1
Y1 - 2023/8/1
N2 - In this paper, by improving the computation efficiency (CE) and ensuring the fairness among users, we study the CE optimization for millimeter-wave mobile edge computing (mmWave-MEC) Networks with NOMA, where both the analog beamforming (ABF) and hybrid beamforming (HBF) architectures under the partial offloading mode are considered. Firstly, according to the max-min fairness criterion, the CE maximization problem is formulated to jointly optimize the ABF and the local resource allocation of each user. An efficient CE optimization algorithm based on the penalized successive convex approximation is proposed to solve this non-convex problem. Then, the max-min CE optimization problem in mmWave-MEC with HBF is studied, where the joint design of the HBF and the local resource allocation of each user is carried out. By using the penalty function and the inexact block coordinate descent method, a feasible CE optimization algorithm is developed to tackle this challenging problem. Simulation results verify the convergence of the proposed algorithms and show that the proposed computation-efficient resource allocation schemes can improve the CE effectively, and mmWave-MEC with HBF can obtain higher CE than that with ABF. Besides, the NOMA scheme exhibits superior performance over the conventional orthogonal multiple access scheme in terms of CE.
AB - In this paper, by improving the computation efficiency (CE) and ensuring the fairness among users, we study the CE optimization for millimeter-wave mobile edge computing (mmWave-MEC) Networks with NOMA, where both the analog beamforming (ABF) and hybrid beamforming (HBF) architectures under the partial offloading mode are considered. Firstly, according to the max-min fairness criterion, the CE maximization problem is formulated to jointly optimize the ABF and the local resource allocation of each user. An efficient CE optimization algorithm based on the penalized successive convex approximation is proposed to solve this non-convex problem. Then, the max-min CE optimization problem in mmWave-MEC with HBF is studied, where the joint design of the HBF and the local resource allocation of each user is carried out. By using the penalty function and the inexact block coordinate descent method, a feasible CE optimization algorithm is developed to tackle this challenging problem. Simulation results verify the convergence of the proposed algorithms and show that the proposed computation-efficient resource allocation schemes can improve the CE effectively, and mmWave-MEC with HBF can obtain higher CE than that with ABF. Besides, the NOMA scheme exhibits superior performance over the conventional orthogonal multiple access scheme in terms of CE.
KW - Millimeter wave communication
KW - Mobile edge computing
KW - NOMA
KW - Optimization
KW - Resource management
KW - Servers
KW - Simulation
KW - Task analysis
KW - computation efficiency
KW - millimeter-wave communications
KW - non-orthogonal multiple access
KW - resource allocation
UR - http://www.scopus.com/inward/record.url?scp=85127773854&partnerID=8YFLogxK
U2 - 10.1109/TMC.2022.3164974
DO - 10.1109/TMC.2022.3164974
M3 - Article
SN - 1536-1233
VL - 22
SP - 4578
EP - 4593
JO - IEEE Transactions on Mobile Computing
JF - IEEE Transactions on Mobile Computing
IS - 8
ER -