Computation Efficiency Maximization in Wireless-Powered Mobile Edge Computing Networks
Computation Efficiency Maximization in Wireless-Powered Mobile Edge Computing Networks
复制标题
无线供电移动边缘计算网络的计算效率最大化
DOI：
10.1109/twc.2020.2970920
复制
发表时间：
2020
影响因子：
10.4
通讯作者：
Hu Rose Qingyang
中科院分区：
文献类型：
--
作者：
Zhou Fuhui;Hu Rose Qingyang
节能计算是移动边缘计算（MEC）网络的必然趋势。最大化计算效率的资源分配策略至关重要。本文提出了无线供电 MEC 网络在部分和二进制计算卸载模式下的计算效率最大化问题。考虑实用的非线性能量收集模型。时分多址 (TDMA) 和非正交多址 (NOMA) 都被考虑和评估用于卸载。能量收集时间、本地计算频率以及卸载时间和功率联合优化，以在最大最小公平准则下最大化计算效率。分别提出了两种迭代算法和两种替代优化算法来解决本文提出的非凸问题。仿真结果表明，所提出的资源分配方案在用户公平性方面优于基准方案。此外，阐明了可实现的计算效率和计算位数之间的权衡。此外，仿真结果表明，部分计算卸载模式优于二进制计算卸载模式，并且 NOMA 在计算效率方面优于 TDMA。
Energy-efficient computation is an inevitable trend for mobile edge computing (MEC) networks. Resource allocation strategies for maximizing the computation efficiency are critically important. In this paper, computation efficiency maximization problems are formulated in wireless-powered MEC networks under both partial and binary computation offloading modes. A practical non-linear energy harvesting model is considered. Both time division multiple access (TDMA) and non-orthogonal multiple access (NOMA) are considered and evaluated for offloading. The energy harvesting time, the local computing frequency, and the offloading time and power are jointly optimized to maximize the computation efficiency under the max-min fairness criterion. Two iterative algorithms and two alternative optimization algorithms are respectively proposed to address the non-convex problems formulated in this paper. Simulation results show that the proposed resource allocation schemes outperform the benchmark schemes in terms of user fairness. Moreover, a tradeoff is elucidated between the achievable computation efficiency and the total number of computed bits. Furthermore, simulation results demonstrate that the partial computation offloading mode outperforms the binary computation offloading mode and NOMA outperforms TDMA in terms of computation efficiency.