Low-Complexity 6DMA Rotation and Position Optimization Based on Statistical Channel Information

The six-dimensional movable antenna (6DMA) is a promising technology to fully exploit spatial variation in wireless channels by allowing flexible adjustment of three-dimensional (3D) positions and rotations of antennas at the transceiver. In this paper, we consider a 6DMA-equipped base station (BS) and aim to maximize the average sum logarithmic rate of all users served by the BS by jointly designing 6DMA surface positions and rotations based on statistical channel information (SCI). Different from prior works on 6DMA design which use alternating optimization to iteratively update surface positions and rotations, we propose a new sequential optimization method that first determines the optimal rotations and then identifies feasible positions to realize these rotations under practical antenna placement constraints. Simulation results show that our proposed optimization scheme significantly reduces the computational complexity of conventional alternating optimization (AO), while achieving communication performance comparable to the AO-based approach and superior to existing fixed-position/rotation antenna arrays.