  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.
