This paper investigates a rotatable antenna (RA) assisted mobile edge computing (MEC) network, where multiple users offload their computation tasks to an edge server equipped with an RA array under a time-division multiple access protocol. To maximize the weighted sum computation rate, we formulate a joint optimization problem over the RA rotation angles, time-slot allocation, transmit power, and local CPU frequencies. Due to the non-convex nature of the formulated problem, a scenario-adaptive hybrid optimization algorithm is proposed. Specifically, for the dynamic rotating scenario, where RAs can flexibly reorient within each time slot, we derive closed-form optimal antenna pointing vectors to enable a low-complexity sequential solution. In contrast, for the static rotating scenario where RAs maintain a unified orientation, we develop an alternating optimization framework, where the non-convex RA rotation constraints are handled using successive convex approximation iteratively with the resource allocation. Simulation results demonstrate that the proposed RA assisted MEC network significantly outperforms conventional fixed-antenna MEC networks. Owing to the additional spatial degrees of freedom introduced by mechanical rotation, the flexibility of RAs effectively mitigates the severe beam misalignment inherent in fixed-antenna systems, particularly under high antenna directivity.

翻译：本文研究了一种可旋转天线辅助的移动边缘计算网络，其中多个用户在时分多址协议下，将计算任务卸载至配备可旋转天线阵列的边缘服务器。为最大化加权总计算速率，我们构建了一个关于可旋转天线转角、时隙分配、发射功率及本地CPU频率的联合优化问题。鉴于该问题的非凸特性，本文提出了一种场景自适应的混合优化算法。具体而言，针对可旋转天线能在每个时隙内灵活调整指向的动态旋转场景，我们推导出闭式最优天线指向向量，从而实现低复杂度顺序求解。与之相对，针对可旋转天线保持统一指向的静态旋转场景，我们开发了一种交替优化框架，其中非凸的可旋转天线旋转约束通过逐次凸逼近与资源分配进行迭代处理。仿真结果表明，所提出的可旋转天线辅助移动边缘计算网络性能显著优于传统固定天线移动边缘计算网络。得益于机械旋转引入的额外空间自由度，可旋转天线的灵活性有效缓解了固定天线系统固有的严重波束失准问题，在高天线方向性条件下尤为明显。