AI 中文总结
针对稀疏阵列的旁瓣与可旋转天线的控制开销问题，提出感知组的稀疏可旋转天线架构，联合优化相关参数，性能接近全共享基准且优于紧凑全向稀疏阵列方案。
AI 中文摘要
稀疏阵列在保留大有效孔径的同时降低了超大规模多输入多输出系统的硬件成本，但可能面临严重的旁瓣与栅瓣泄漏问题。可旋转天线（RA）可提供定向泄漏抑制，不过频繁调整视轴以适配瞬时用户位置会产生可观的控制开销。实际场景中，长期用户分布往往非均匀，紧凑的热点区域与分散用户共存，这使得可基于组级几何结构实现低复杂度的可旋转天线配置。受此观察启发，我们提出一种感知组的稀疏可旋转天线架构，其中用户被划分为服务组，激活的可旋转天线被划分为各组专属的稀疏子阵列。我们通过联合优化稀疏孔径分配、可旋转天线方向及发射波束成形，最大化所有用户的最小信干噪比（SINR）。研究表明，可旋转天线诱导的组间泄漏抑制与稀疏孔径诱导的组内正交化共同产生近似解耦的组级波束成形结构，为组级天线数量分配及非周期稀疏位置初始化提供物理指导。基于这些见解，我们开发了一种结构化低复杂度两层算法，该算法将闭式投影组中心可旋转天线方向规则嵌入稀疏孔径分配与波束成形设计中，算法结合了分析引导初始化、采样多起点天线分配搜索及基于二分法的二阶锥规划来实现波束成形。数值结果显示，所提设计与全共享且方向优化的基准方案性能接近，同时大幅优于紧凑全向稀疏阵列方案。
英文摘要
Sparse rotatable array (SRA) is a novel reconfigurable antenna architecture that jointly exploits sparse aperture configuration and antenna directivity to enhance spatial resolution for future wireless communications. Specifically, SRA activates a subset of rotatable antennas over a large candidate aperture and adjusts their boresight directions, thereby creating a directionally selective sparse aperture with reduced hardware requirements and enhanced spatial flexibility. In this paper, we investigate an SRA-aided multi-group communication system, where users are organized into spatial groups with different service requirements. We develop a group-aware SRA design framework by jointly optimizing the sparse-aperture allocation, RA orientations, and transmit beamforming to maximize the weighted max-min signal-to-interference-plus-noise ratio (SINR). Then, we characterize the operating principles of SRA and reveal that sparse aperture improves spatial resolution by enlarging the effective array aperture, while antenna directivity suppresses inter-group coupling through directional control, thereby enabling simplified group-wise beamforming structures. Guided by these insights, we develop a structured low-complexity alternating optimization algorithm that embeds a closed-form projected group-center RA orientation rule into the sparse-aperture allocation and beamforming design. The proposed algorithm combines analysis-guided initialization, sampled multi-start antenna-allocation search, and bisection-based second-order cone programming for beamforming. Numerical results show that the proposed SRA design closely approaches fully-shared SRA benchmarks and significantly outperforms compact subarray and omni sparse-array schemes.
