🤖 AI Summary
This work addresses the limited adaptability of conventional MIMO systems, whose fixed antenna arrays hinder dynamic optimization of channel capacity in varying propagation environments. For the first time, the physical orientation of antennas is introduced as a new degree of freedom, enabling the development of a channel model with rotatable antennas. The authors jointly optimize the transmit covariance matrix and the antenna pointing directions at both transmitter and receiver under a spherical cap constraint to maximize channel capacity. To tackle this non-convex problem, an alternating optimization algorithm is proposed, integrating eigenmode transmission, water-filling, and Riemannian Frank–Wolfe methods. A simplified design is also derived for the low-SNR regime. Numerical results demonstrate that the proposed approach significantly outperforms fixed-orientation baselines, confirming the efficacy and potential of orientation-aware channel reconfiguration.
📝 Abstract
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.