Active Reconfigurable Intelligent Surface for Mobile Edge Computing
원문 초록
This paper investigates an active reconfigurable intelligent surface (RIS)-aided mobile edge computing (MEC) system. Compared with passive RIS, the active RIS is equipped with active reflective amplifier, which can effectively circumvent the "double path loss" attenuation. We propose a joint computing and communication design to minimize the maximum computational latency (MCL), subject to both the phase shift constraints and the edge computing capability constraints. Specifically, the original problem is decoupled into four subproblems, and then the block coordinate descent (BCD) method and the successive convex approximation (SCA) method are applied to alternately optimize the subproblems. The simulation results show that with the same power budget, the performance gain achieved by the active RIS is much larger than that by the passive RIS.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Agile Reinforcement Learning for Real-Time Task Scheduling in Edge Computing
Edge-Enabled Collaborative Object Detection for Real-Time Multi-Vehicle Perception
FedSKC: Federated Learning with Non-IID Data via Structural Knowledge Collaboration
The More is not the Merrier: Investigating the Effect of Client Size on Federated Learning
Cooperative Inference for Real-Time 3D Human Pose Estimation in Multi-Device Edge Networks
PolygoNet: Leveraging Simplified Polygonal Representation for Effective Image Classification
토론
이 논문과 연결된 포럼 글이 아직 없습니다.