Fluid Antenna for Mobile Edge Computing
Yiping Zuo, Jiajia Guo, Biyun Sheng, Chen Dai, Fu Xiao, Shi Jin
TL;DR
This work tackles end-to-end latency in mobile edge computing by leveraging fluid antenna mobility at the base station to improve uplink channels. It formulates a joint optimization problem over antenna positions, offloading ratios, and MEC CPU frequencies, and solves it with an alternating IPPSO algorithm that combines interior-point optimization for continuous variables with particle swarm optimization for antenna placement. Numerical results show that moving FAs within a local domain yields notable transmission-rate gains and latency reductions compared with fixed-antennas baselines, with robust and fast convergence of the proposed method. The approach demonstrates the practical potential of fluid antennas to enhance MEC service quality under SDMA uplink scenarios.
Abstract
In the evolving environment of mobile edge computing (MEC), optimizing system performance to meet the growing demand for low-latency computing services is a top priority. Integrating fluidic antenna (FA) technology into MEC networks provides a new approach to address this challenge. This letter proposes an FA-enabled MEC scheme that aims to minimize the total system delay by leveraging the mobility of FA to enhance channel conditions and improve computational offloading efficiency. By establishing an optimization problem focusing on the joint optimization of computation offloading and antenna positioning, we introduce an alternating iterative algorithm based on the interior point method and particle swarm optimization (IPPSO). Numerical results demonstrate the advantages of our proposed scheme compared to traditional fixed antenna positions, showing significant improvements in transmission rates and reductions in delays. The proposed IPPSO algorithm exhibits robust convergence properties, further validating the effectiveness of our method.