This paper investigates the utility of the movable antenna (MA) and reconfigurable intelligent surface (RIS) framework for downlink wireless communications. In the considered scenario, a base station (BS) is equipped with two sub-arrays of MAs transmits signals to the users via the RIS. By jointly exploiting the antenna-positioning flexibility of MAs and the RIS element selection capability, the proposed joint MA-RIS framework introduces additional design degrees of freedom to enhance desired signals and mitigate inter-user interference, thereby maximizing the network sum-rate. To this end, we formulate a joint optimization problem involving MA positioning, sub-array beamforming, and RIS element selection, subject to the minimum antenna separation and transmit power constraints. The resulting problem is highly non-convex and challenging to solve directly. To address this issue, an alternating optimization framework is developed that decomposes the problem into three tractable subproblems. Specifically, zero-forcing beamforming is employed for transmit beamformer design, a low-complexity one-dimensional search is derived for RIS element selection, and the MA positioning problem is solved using block coordinate descent (BCD) and convex optimization techniques implemented via CVX. Simulation results demonstrate that the proposed joint MA-RIS framework significantly improves the achievable sum-rate compared with conventional fixed MAs and benchmark schemes with random configurations.

翻译：本文研究了可移动天线（MA）与可重构智能表面（RIS）框架在下行无线通信中的应用。在所考虑的系统中，配备两个MA子阵列的基站通过RIS向用户传输信号。通过联合利用MA的天线位置灵活性和RIS单元选择能力，所提出的MA-RIS联合框架引入了额外的设计自由度，可增强期望信号并抑制用户间干扰，从而最大化网络和速率。为此，我们在最小天线间距和发射功率约束下，构建了一个涉及MA定位、子阵列波束成形和RIS单元选择的联合优化问题。该问题具有高度非凸性，直接求解较为困难。针对此问题，本文提出了一种交替优化框架，将原问题分解为三个可解子问题：采用迫零波束成形设计发射波束赋形器，通过低复杂度一维搜索实现RIS单元选择，并利用块坐标下降（BCD）和基于CVX实现的凸优化技术求解MA定位问题。仿真结果表明，与采用固定天线配置的传统方案及随机配置的基准方案相比，所提出的MA-RIS联合框架能够显著提升可实现的和速率。