Mobile edge computing (MEC) provides wireless devices (WDs) more computing capability and lower latency by allowing them to offload their computation tasks to a nearby more powerful server. Furthermore, adopting the relaying technique can effectively improve the offloading performance, especially when the wireless channel conditions between WD and MEC server are poor. In this article, we consider a multiuser relay-aided MEC system targeting at minimizing the energy consumption. The relay can either execute the computation task by itself or offload the task to the MEC server. Under the partial computation offloading mode, an energy minimization problem is investigated by jointly optimizing transmit power, offloading time duration, and central processing unit (CPU) frequencies. To solve the nonconvex optimization problem, an iterative algorithm based on successive convex approximation (SCA) is developed. Furthermore, the closed-form expressions for the optimal transmission powers and the CPU frequencies are derived. The simulation results show that the proposed scheme can achieve a lower energy consumption than other benchmark schemes.

中文翻译：

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中继辅助移动边缘计算系统中的资源分配


移动边缘计算 (MEC) 允许无线设备 (WD) 将计算任务卸载到附近更强大的服务器，从而为无线设备 (WD) 提供更多的计算能力和更低的延迟。此外，采用中继技术可以有效提高卸载性能，特别是当WD和MEC服务器之间的无线信道条件较差时。在本文中，我们考虑了一种旨在最大限度地减少能耗的多用户中继辅助 MEC 系统。中继可以自行执行计算任务，也可以将任务卸载到 MEC 服务器。在部分计算卸载模式下，通过联合优化发射功率、卸载持续时间和中央处理器（CPU）频率来研究能量最小化问题。为了解决非凸优化问题，开发了一种基于逐次凸逼近（SCA）的迭代算法。此外，还推导了最佳传输功率和CPU频率的封闭式表达式。仿真结果表明，所提出的方案可以实现比其他基准方案更低的能耗。