Movable antennas (MAs) are a promising paradigm to enhance the spatial degrees of freedom of conventional multi-antenna systems by flexibly adapting the positions of the antenna elements within a given transmit area. In this paper, we model the motion of the MA elements as discrete movements and study the corresponding resource allocation problem for MA-enabled multiuser multiple-input single-output (MISO) communication systems. Specifically, we jointly optimize the beamforming and the MA positions at the base station (BS) for the minimization of the total transmit power while guaranteeing the minimum required signal-to-interference-plus-noise ratio (SINR) of each individual user. To obtain the globally optimal solution to the formulated resource allocation problem, we develop an iterative algorithm capitalizing on the generalized Bender's decomposition with guaranteed convergence. Our numerical results demonstrate that the proposed MA-enabled communication system can significantly reduce the BS transmit power and the number of antenna elements needed to achieve a desired performance compared to state-of-the-art techniques, such as antenna selection. Furthermore, we observe that refining the step size of the MA motion driver improves performance at the expense of a higher computational complexity.

翻译：可移动天线（MA）通过灵活调整给定发射区域内天线单元的位置，为增强传统多天线系统的空间自由度提供了一种有前景的范式。本文中，我们将MA单元的运动建模为离散移动，并研究MA赋能的多用户多输入单输出（MISO）通信系统中的相应资源分配问题。具体而言，我们在基站（BS）处联合优化波束赋形和MA位置，以最小化总发射功率，同时保证每个用户所需的最小信干噪比（SINR）。为了获得所制定资源分配问题的全局最优解，我们开发了一种基于广义Benders分解的迭代算法，该算法具有收敛性保证。数值结果表明，与天线选择等现有技术相比，所提出的MA赋能通信系统能够显著降低实现期望性能所需的BS发射功率和天线单元数量。此外，我们观察到细化MA运动驱动器的步长能够提升性能，但会带来更高的计算复杂度。