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.

翻译：在移动边缘计算（MEC）不断发展的环境中，优化系统性能以满足日益增长的低延迟计算服务需求是首要任务。将流体天线（FA）技术集成到MEC网络中，为解决这一挑战提供了新思路。本文提出一种FA赋能的MEC方案，旨在通过利用FA的移动性增强信道条件并提升计算卸载效率，从而最小化系统总时延。通过建立联合优化计算卸载与天线定位的优化问题，我们引入了一种基于内点法和粒子群优化（IPPSO）的交替迭代算法。数值结果表明，与传统固定天线位置相比，所提方案在传输速率提升和时延降低方面具有显著优势。提出的IPPSO算法展现出鲁棒的收敛特性，进一步验证了该方法的有效性。