Energy-efficient Resource Allocation for Intelligent Reflecting Surface Aided MEC Networks

Yating Wen, Tongxing Zheng, Yongxia Tong, Xin Chen, Menghan Lin, Wenjie Wang
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Abstract

In this paper, we consider the physical layer security for a mobile edge computing (MEC) network where multiple single-antenna users aim to securely offload partial computation tasks simultaneously to an access point (AP) integrated with an MEC server by leveraging an intelligent reflecting surface (IRS) in the presence of a multi-antenna eavesdropper. A friendly jammer is further introduced to improve transmission secrecy. We formulate a problem of minimizing the sum energy consumption by jointly designing the allocation of computation bits for local computing and offloading, the transmit power of both users and jammer, the multi-user detection matrix at the AP, and the phase shift matrix at the IRS. The formulated problem is a non-convex problem that is hard to tackle directly, so we decompose it into tractable subproblems and develop an alternating optimization approach by combing semidefinite relaxation algorithm. Numerical results are provided to demonstrate the effectiveness of the proposed scheme and the benefit of deploying an IRS for achieving a secure and energy-efficient MEC network.
智能反射面辅助MEC网络的节能资源分配
在本文中,我们考虑了移动边缘计算(MEC)网络的物理层安全性,其中多个单天线用户旨在通过在多天线窃听器存在的情况下利用智能反射面(IRS),同时安全地将部分计算任务卸载到与MEC服务器集成的接入点(AP)。为了提高传输保密性,进一步引入了友好型干扰机。通过共同设计本地计算和卸载的计算位分配、用户和干扰机的发射功率、AP处的多用户检测矩阵和IRS处的相移矩阵,提出了最小化总能耗的问题。该问题是一个难以直接求解的非凸问题,因此我们将其分解为可处理的子问题,并结合半定松弛算法开发了一种交替优化方法。数值结果证明了该方案的有效性,以及部署IRS对实现安全节能的MEC网络的好处。
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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