[论文解读] Empowering Mobile Edge Computing by Exploiting Reconfigurable Intelligent Surface

Tong Bai, Cunhua Pan+2 more|arXiv (Cornell University)|Feb 4, 2021

Advanced Wireless Communication Technologies参考文献 7被引用 11

一句话总结

本文提出将可重构智能表面（RIS）集成到移动边缘计算（MEC）系统中，通过动态优化无线传播环境来增强计算卸载链路。通过联合优化RIS相位移、通信资源和计算分配，该方法显著提升了卸载可靠性和系统性能，案例研究验证了其在能效和任务完成率方面实现显著提升。

ABSTRACT

Along with the proliferation of sensors and of smart devices, an explosive volume of data will be generated. However, restricted by their limited physical sizes and low manufacturing costs, these wireless devices are typically equipped with limited computational capabilities and battery lives and thus incapable of processing data time-efficiently. To overcome this issue, the paradigm of mobile edge computing (MEC) is proposed, where wireless devices may offload all or a fraction of their computation tasks to their nearby computing nodes deployed at the network edge. At the time of writing, the benefits of MEC systems have not been fully exploited, predominately because the computation offloading link is still far from the perfect. In this article, we propose to empower the MEC systems by exploiting the emerging technique of reconfigurable intelligent surfaces, which is capable of reconfiguring the wireless propagation environments and hence of enhancing the offloading links. The beneficial role of RISs can be exploited by jointly optimizing both the RISs as well as communications and computing resource allocations of MEC systems, which imposes new research challenges on the systemic design and thus necessitates a specific investigation. Against this background, this article provides an overview of RIS-assisted MEC systems and highlights their four use cases as well as their design challenges and solutions. Then their advantageous performance is validated with the aid of a specific case study. Finally, a guide on future research opportunities is elucidated.

研究动机与目标

• 解决密集物联网和传感器网络中无线设备计算能力有限和电池寿命短的问题。
• 克服现有MEC系统因计算卸载链路不可靠而导致的性能瓶颈。
• 利用可重构智能表面（RIS）动态调控无线传播环境，改善链路质量。
• 联合优化RIS配置、通信资源和计算分配，以最大化MEC系统效率。
• 识别并解决将RIS集成到MEC架构中所引入的新系统级设计挑战。

提出的方法

• 引入RIS作为动态波前整形平台，以增强MEC中计算卸载的无线信道质量。
• 构建一个涉及RIS相位移、上行链路发射功率和任务卸载比例的联合优化问题。
• 将通信与计算资源分配整合到统一的优化框架中，以最小化系统时延和能耗。
• 应用信号处理技术，将RIS辅助的无线信道建模为可重构反射矩阵。
• 通过案例研究验证所提出的RIS辅助MEC框架在真实网络条件下的性能增益。
• 提出一种解决方案框架，平衡RIS赋能MEC系统中的频谱效率、能效和任务完成可靠性。

实验结果

研究问题

• RQ1 如何利用RIS提升MEC系统中计算卸载链路的可靠性和容量？
• RQ2 何种联合优化策略可同时控制MEC中的RIS相位移、通信资源和计算分配？
• RQ3 将RIS集成到MEC架构中会引入哪些关键系统级挑战？
• RQ4 与传统MEC相比，RIS辅助MEC在能效和任务完成时延方面表现如何？
• RQ5 评估RIS赋能MEC系统时，哪些设计原则和性能指标最为相关？

主要发现

• 将RIS集成到MEC系统中可显著提升计算卸载链路的可靠性和频谱效率。
• 联合优化RIS相位移、发射功率和任务卸载比例可显著降低系统时延和能耗。
• 案例研究显示，所提框架在非视 Line-of-Sight 或低信噪比环境下，能效和任务完成率均得到明显提升。
• RIS可实现更可预测和可控的无线传播，减轻密集设备部署中的多径衰落和阴影效应。
• 在设备密度高且无线资源受限的场景下，系统性能增益更为显著。
• RIS赋能MEC的设计挑战具有非平凡性，需协同设计通信、计算与智能表面控制机制。