Mobile edge computing (MEC) enables users to offload their computation-intensive and latency-sensitive tasks to edge servers. Based on MEC, users can reduce their energy consumption and guarantee latency in executing computational tasks. However, current terrestrial MEC networks have some disadvantages, such as fixed deployed infrastructure and severe signal attenuation. Recently, a new paradigm of reconfigurable intelligent surface (RIS)-assisted wireless networks has drawn extensive attention due to its low cost but high spectral and energy efficiencies. This article introduces the use of aerial RIS (ARIS) mounted on an unmanned aerial vehicle (UAV) into MEC, which achieves three-dimensional signal reflections in the uplink computation offloading. The network performance can be improved by designing the communication and computation resource allocation, the ARIS's trajectory, and the amplitudes and phase shifts of passive reflecting elements. However, there are some issues that must be addressed for the ARIS-assisted MEC, including resource allocation and trajectory design, ARIS beamforming design with imperfect channel state information, and the trade-off between the non-line-of-sight excessive path loss and the doubled path loss. This article presents the motivation, applications, challenges, and opportunities of introducing ARISs into MEC. Moreover, numerical results are provided to showcase potential performance enhancement using ARISs in MEC networks.
All Science Journal Classification (ASJC) codes
- Computer Science Applications
- Electrical and Electronic Engineering
- Autonomous aerial vehicles
- Energy consumption
- Resource management
- Task analysis