Conventional multiple-input multiple-output (MIMO) systems mainly rely on fixed antenna arrays, which limits their capability to adapt the effective channel matrix to the propagation environment. Rotatable antennas (RAs), which enable mechanical or electronic adjustment of antenna boresight directions, introduce a new orientation-domain degree of freedom for channel reconfiguration. In this paper, we investigate an RA-aided MIMO communication system for channel capacity enhancement. We first establish an orientation-dependent MIMO channel model. Then, we formulate a capacity maximization problem by jointly optimizing the transmit covariance matrix and the transmit/receive RA orientations under practical spherical-cap constraints. To solve this non-convex problem, we develop an alternating optimization algorithm, where the transmit covariance matrix is updated via eigenmode transmission and water-filling, while each RA orientation is optimized through a Riemannian Frank-Wolfe method. We further investigate the low-SNR regime and derive simplified designs for multiple-input single-output (MISO) and single-input multiple-output (SIMO) special cases. Numerical results show that the proposed RA-aided MIMO design significantly improves the channel capacity compared with the fixed-orientation benchmark, demonstrating the benefits of orientation-domain channel reconfiguration.

翻译：传统多输入多输出（MIMO）系统主要依赖固定天线阵列，限制了其根据传播环境调整有效信道矩阵的能力。可旋转天线（RA）能够以机械或电子方式调整天线波束指向方向，为信道重构引入了定向域自由度。本文研究基于RA辅助的MIMO通信系统以提升信道容量。首先建立与定向相关的MIMO信道模型，随后在实际球冠约束条件下通过联合优化发射协方差矩阵与收发RA定向，构建容量最大化问题。为求解该非凸问题，开发了交替优化算法——通过特征模态传输和注水算法更新发射协方差矩阵，同时利用黎曼Frank-Wolfe方法优化每个RA的定向。进一步分析低信噪比（SNR）场景，并为多输入单输出（MISO）与单输入多输出（SIMO）特殊情况推导简化设计。数值结果表明，相较于固定定向基准方案，所提RA辅助MIMO设计显著提升信道容量，验证了定向域信道重构的优越性。