This letter proposes a hybrid mechanically and electronically tunable six-dimensional movable antenna (6DMA) base station (BS) architecture for future wireless communication networks. Such BS consists of multiple antenna arrays that are mechanically movable along a circular rail to adapt to the horizontal user hotspots, and each array is equipped with pattern reconfigurable antennas (PRAs) that are capable of electronically switching among a set of specified beam patterns to cater to the instantaneous user channels. The mechanical adjustment provides wide-angle coverage but suffers from slow response, while the electronic tuning enables rapid beam reconfiguration but with limited angular range. To effectively combine their complementary advantages, we propose to jointly design both mechanical and electronic configurations to maximize the average sum-rate of users via a two-timescale optimization approach, in which the array positions are optimized on the long timescale according to large-scale user distribution statistics, and the pattern selection vectors are optimized on the short timescale to enable fast beam alignment based on the instantaneous user locations. An alternating optimization algorithm based on the Monte Carlo sampling method is developed to solve the problem efficiently. Finally, simulation results show that our proposed design achieves significant performance gains over various benchmark schemes.

翻译：本文提出了一种面向未来无线通信网络的混合机械与电子可调谐六维移动天线基站架构。该基站由多个天线阵列构成，这些阵列可沿圆形轨道机械移动以适应水平方向的用户热点区域；每个阵列配备方向图可重构天线，能够通过电子方式在一组预设波束方向图中快速切换，以适应瞬时用户信道。机械调节可提供大角度覆盖但响应速度较慢，而电子调谐能实现快速波束重构但角度范围有限。为有效结合二者的互补优势，我们提出通过双时间尺度优化方法联合设计机械与电子配置，以最大化用户的平均和速率。其中，阵列位置根据大规模用户分布统计信息在长时间尺度进行优化，而方向图选择向量则在短时间尺度进行优化，以实现基于瞬时用户位置的快速波束对准。本文开发了一种基于蒙特卡洛采样方法的交替优化算法以高效求解该问题。仿真结果表明，所提设计方案相较于多种基准方案均能实现显著的性能增益。