论文标题
无线动力移动边缘计算网络中的计算效率最大化
Computation Efficiency Maximization in Wireless-Powered Mobile Edge Computing Networks
论文作者
论文摘要
节能计算是移动边缘计算（MEC）网络的不可避免的趋势。最大化计算效率的资源分配策略至关重要。在本文中，在部分和二进制计算卸载模式下，计算效率最大化问题是在无线供电的MEC网络中提出的。考虑了实用的非线性能量收集模型。考虑并评估了时间划分多重访问（TDMA）和非正交多重访问（NOMA）的卸载。能源收集时间，本地计算频率以及卸载时间和功率被共同优化，以最大化最大值的计算效率。提出了两种迭代算法和两种替代优化算法，以解决本文中提出的非凸问题。仿真结果表明，所提出的资源分配方案在用户公平方面优于基准方案。此外，在可实现的计算效率和计算位总数之间阐明了权衡。此外，模拟结果表明，部分计算卸载模式优于二进制计算卸载模式，而NOMA在计算效率方面的表现优于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.
