论文标题
智能反射表面的强大设计辅助味o系统
Robust Design for Intelligent Reflecting Surfaces Assisted MISO Systems
论文作者
论文摘要
在这项工作中，我们研究了在不完美的通道状态信息（CSI）下，智能反射表面（IRS）辅助多重输入单输出（MISO）无线系统的统计上强大的波束形成设计，其中假定通道估计误差为附加性高斯。我们旨在共同优化发射/接收波束形式和IRS相移，以最大程度地减少用户的平均平方误差（MSE）。特别是，为了解决非凸优化问题，通过利用交替优化和大型最小化技术来开发有效的算法。仿真结果表明，在存在CSI误差的情况下，所提出的方案实现了稳健的MSE性能，并且显着优于常规的非稳定方法。
In this work, we study the statistically robust beamforming design for an intelligent reflecting surfaces (IRS) assisted multiple-input single-output (MISO) wireless system under imperfect channel state information (CSI), where the channel estimation errors are assumed to be additive Gaussian. We aim at jointly optimizing the transmit/receive beamformers and IRS phase shifts to minimize the average mean squared error (MSE) at the user. In particular, to tackle the non-convex optimization problem, an efficient algorithm is developed by capitalizing on alternating optimization and majorization-minimization techniques. Simulation results show that the proposed scheme achieves robust MSE performance in the presence of CSI error, and substantially outperforms conventional non-robust methods.
