Fluid antennas (FAs) and movable antennas (MAs) have emerged as promising technologies in wireless communications, which offer the flexibility to improve channel conditions by adjusting transmit/receive antenna positions within a spatial region. In this letter, we focus on an MA-enhanced multiple-input single-output (MISO) communication system, aiming to optimize the positions of multiple transmit MAs to maximize the received signal power. Unlike the prior works on continuously searching for the optimal MA positions, we propose to sample the transmit region into discrete points, such that the continuous antenna position optimization problem is transformed to a discrete sampling point selection problem based on the point-wise channel information. However, such a point selection problem is combinatory and challenging to be optimally solved. To tackle this challenge, we ingeniously recast it as an equivalent fixed-hop shortest path problem in graph theory and propose a customized algorithm to solve it optimally in polynomial time. To further reduce the complexity, a linear-time sequential update algorithm is also proposed to obtain a high-quality suboptimal solution. Numerical results demonstrate that the proposed algorithms can yield considerable performance gains over the conventional fixed-position antennas with/without antenna selection.

翻译：流体天线（FA）与可移动天线（MA）作为无线通信领域的新兴技术，通过调整空间区域内收发天线位置，展现出改善信道条件的灵活性。本文聚焦于MA增强型多输入单输出（MISO）通信系统，旨在通过优化多个发射MA的位置实现接收信号功率最大化。与现有持续搜索最优MA位置的研究不同，本文将发射区域离散化为采样点，将连续天线位置优化问题转化为基于点对点信道信息的离散采样点选择问题。然而该点选择问题具有组合优化特性，难以求得最优解。为应对这一挑战，本文巧妙地将该问题重构为图论中的等阶固定跳数最短路径问题，并提出定制化算法在多项式时间内实现最优求解。为进一步降低复杂度，本文还提出线性时间序贯更新算法以获取高质量次优解。数值结果表明，与传统固定位置天线（含/不含天线选择）相比，所提算法可获得显著性能增益。