论文标题
智能反射表面辅助的毫米波模拟系统的频道估计
Channel Estimation for Intelligent Reflecting Surface-Assisted Millimeter Wave MIMO Systems
论文作者
论文摘要
智能反射表面（IRS）被认为是未来毫米波（MMWave）无线通信的有前途的推动者，因为它们能够创建有利的视线（LOS）传播环境。在本文中，我们研究了下行链路IRS辅助MMWAVE多输入多输出（MIMO）系统中的通道估计。通过利用MMWave通道的稀疏性，我们将通道估计问题提出为固定级限制的非凸优化问题。为了解决非跨性别性，通过利用交替的最小化和多种歧视优化（MO）提出了有效的算法，该算法得出了局部最佳的解决方案。仿真结果表明，提出的基于MO的估计（MO-EST）算法显着胜过两个基准方案，并证明了MO-最新算法在实际实现中通道的稀疏水平方面的鲁棒性。
Intelligent reflecting surfaces (IRSs) are regarded as promising enablers for future millimeter wave (mmWave) wireless communication, due to their ability to create favorable line-of-sight (LoS) propagation environments. In this paper, we investigate channel estimation in downlink IRS-assisted mmWave multiple-input multiple-output (MIMO) systems. By leveraging the sparsity of mmWave channels, we formulate the channel estimation problem as a fixed-rank constrained non-convex optimization problem. To tackle the non-convexity, an efficient algorithm is proposed by capitalizing on alternating minimization and manifold optimization (MO), which yields a locally optimal solution. Simulation results show that the proposed MO-based estimation (MO-EST) algorithm significantly outperforms two benchmark schemes and demonstrate the robustness of the MO-EST algorithm with respect to imperfect knowledge of the sparsity level of the channels in practical implementations.
