Resource Allocation for System Throughput Maximization Based on Mobile Edge Computing

Jianbin Xue, Hua Shao, Qingliu Ma
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引用次数: 4

Abstract

Mobile edge computing (MEC) provides cloud computing capabilities at the edge of the mobile network, emphasizing proximity to mobile users to reduce network operation and service delays, improving user experience. In this paper, we study the problem of low utilization spectrum resources for MEC in 5G heterogeneous networks. We first explore the problem of computing offloading in multi-channel environment. Then an optimization problem is proposed to maximum the overall throughput of the offloading system, where the power control and interference are taken into consideration. We transform the original optimization problem into a convex optimization problem, and use the Lagrangian dual algorithm to establish the KKT condition. By continuous iterative operation, the user's transmit power is optimally achieved. Simulation results show that our proposed scheme not only guarantees the communication quality, but also improves the system throughput and spectrum utilization.
基于移动边缘计算的系统吞吐量最大化资源分配
移动边缘计算(MEC)在移动网络边缘提供云计算能力,强调靠近移动用户,减少网络运营和服务延迟,提升用户体验。本文研究了5G异构网络中MEC频谱资源利用率低的问题。我们首先探讨了多通道环境下的计算卸载问题。在此基础上,提出了考虑功率控制和干扰的卸载系统总吞吐量最大化的优化问题。将原优化问题转化为一个凸优化问题,并利用拉格朗日对偶算法建立了KKT条件。通过连续迭代运算,实现了用户发射功率的最优化。仿真结果表明,该方案不仅保证了通信质量,而且提高了系统吞吐量和频谱利用率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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