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首页> 外文期刊>Wireless Communications Letters, IEEE >Intelligent Reflecting Surface Assisted Mobile Edge Computing for Internet of Things
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Intelligent Reflecting Surface Assisted Mobile Edge Computing for Internet of Things

机译：智能反射表面辅助移动边缘计算用于互联网

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摘要

This letter studies the impact of an intelligent reflecting surface (IRS) on computational performance in a mobile edge computing (MEC) system. Specifically, an access point (AP) equipped with an edge server provides MEC services to multiple Internet of Thing (IoT) devices that choose to offload a portion of their own computational tasks to the AP with the remaining portion being locally computed. We deploy an IRS to enhance the computational performance of the MEC system by intelligently adjusting the phase shift of each reflecting element. A joint design problem is formulated for the considered IRS assisted MEC system, aiming to optimize its sum computational bits and taking into account the CPU frequency, the offloading time allocation, transmit power of each device as well as the phase shifts of the IRS. To deal with the non-convexity of the formulated problem, we conduct our algorithm design by finding the optimized phase shifts first and then achieving the jointly optimal solution of the CPU frequency, the transmit power and the offloading time allocation by considering the Lagrange dual method and Karush-Kuhn-Tucker (KKT) conditions. Numerical evaluations highlight the advantage of the IRS-assisted MEC system in comparison with the benchmark schemes.
机译：这封信研究了智能反射表面（IRS）对移动边缘计算（MEC）系统中的计算性能的影响。具体地，配备有边缘服务器的接入点（AP）向多个事物（IOT）设备提供MEC服务，该设备选择将其自身计算任务的一部分卸载到AP，其中剩余部分是本地计算的。我们通过智能地调​​整每个反射元件的相移来提高MEC系统的计算性能以提高MEC系统的计算性能。对于考虑的IRS辅助MEC系统，配制了联合设计问题，旨在优化其总和计算比特，并考虑到CPU频率，卸载时间分配，每个设备的发射功率以及IRS的相移。要处理配制问题的非凸性，我们首先通过查找优化的相变，然后通过考虑拉格朗日双方法来实现CPU频率，发射功率和卸载时间分配的联合最佳解决方案来进行算法设计和karush-kuhn-tucker（kkt）条件。与基准方案相比，数值评估突出了IRS辅助MEC系统的优势。

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