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arXiv 1809.01430cs.ITmath.IT
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移动边缘计算系统中的无线用户协作计算

Wireless Powered User Cooperative Computation in Mobile Edge Computing Systems

Dixiao Wu, Feng Wang, Xiaowen Cao, Jie Xu

摘要:

本文研究了一种无线供电的移动边缘计算(MEC)系统,其中专用能量发射器(ET)使用射频(RF)信号启用无线功率传输(WPT)为无线设备充电,以实现可持续计算。在这样的系统中,我们提出了一种新的用户合作的方法来提高主动设备的计算性能,其中周围的空闲设备被启用作为助手,使用他们的机会主义收获的无线能量从ET,以帮助远程执行活动用户的计算任务。特别是,我们考虑一个基本的情况下,一个用户(计算任务执行)和多个助手,其中用户可以分区的计算任务分为不同的部分,本地执行和计算卸载到助手,分别。用户和助手都受到所谓的能量中性约束,使得他们的能量消耗不超过从ET收集的相应能量。在这种设置下并考虑基于频分多址(FDMA)的计算卸载协议,我们最大化计算速率(即,特定时间块上的计算比特数),以及用户和助手处的通信和计算资源分配。通过利用拉格朗日对偶方法,我们提出了这个问题的最优解的半封闭形式。数值结果表明,所提出的无线供电用户合作计算的设计显着提高了计算速度的用户,相比传统的计划,没有这样的合作。

英文摘要:

This paper studies a wireless powered mobile edge computing (MEC) system, where a dedicated energy transmitter (ET) uses the radio-frequency (RF) signal enabled wireless power transfer (WPT) to charge wireless devices for sustainable computation. In such a system, we present a new user cooperation approach to improve the computation performance of active devices, in which surrounding idle devices are enabled as helpers to use their opportunistically harvested wireless energy from the ET to help remotely execute active users' computation tasks. In particular, we consider a basic scenario with one user (with computation tasks to execute) and multiple helpers, in which the user can partition the computation tasks into various parts for local execution and computation offloading to helpers, respectively. Both the user and helpers are subject to the so-called energy neutrality constraints, such that their energy consumption does not exceed the respective energy harvested from the ET. Under this setup and considering a frequency division multiple access (FDMA) based computation offloading protocol, we maximize the computation rate (i.e., the number of computation bits over a particular time block) of the user, by jointly optimizing the transmit energy beamforming at the ET, as well as the communication and computation resource allocations at both the user and helpers. By leveraging the Lagrange duality method, we present the optimal solution to this problem in a semi-closed form. Numerical results show that the proposed wireless powered user cooperative computation design significantly improves the computation rate at the user, as compared to conventional schemes without such cooperation.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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