论文标题
RIS辅助通信系统的联合波束形成设计和3D DOA估计
Joint Beamforming Design and 3D DoA Estimation for RIS-aided Communication System
论文作者
论文摘要
在本文中，我们考虑了可重新配置的智能表面（RIS）辅助3D排序方向（DOA）估计系统，其中部署了一个均匀的平面阵列（UPA）RIS，以提供虚拟的视线（LOS）链接并反映上UPLINK PILOT信号向传感器。为了克服RIS和DOA估计的波束形成设计之间的相互耦合问题，我们探索了可分离的稀疏表示结构，并提出了交替的优化算法。基于网格的DOA估计是考虑到网格偏置的联合恢复问题的建模，并且使用inter-2d-omp方法来估计网格和离网部件。得出相应的cramér-rao下限（CRLB）以评估估计值。然后，根据估计的角度优化了RIS处的Beampattern在传感器处最大化信噪比（SNR）。数值结果表明，与随机波束形成设计的基准相比，提出的交替优化算法可以达到较低的估计误差。
In this paper, we consider a reconfigurable intelligent surface (RIS)-assisted 3D direction-of-arrival (DoA) estimation system, in which a uniform planar array (UPA) RIS is deployed to provide virtual line-of-sight (LOS) links and reflect the uplink pilot signal to sensors. To overcome the mutually coupled problem between the beamforming design at the RIS and DoA estimation, we explore the separable sparse representation structure and propose an alternating optimization algorithm. The grid-based DoA estimation is modeled as a joint-sparse recovery problem considering the grid bias, and the Joint-2D-OMP method is used to estimate both on-grid and off-grid parts. The corresponding Cramér-Rao lower bound (CRLB) is derived to evaluate the estimation. Then, the beampattern at the RIS is optimized to maximize the signal-to-noise (SNR) at sensors according to the estimated angles. Numerical results show that the proposed alternating optimization algorithm can achieve lower estimation error compared to benchmarks of random beamforming design.
