Intelligent reflection surface (IRS) has recently been recognized as a promising technique to enhance the performance of wireless systems due to its ability of reconfiguring the signal propagation environment. However, the perfect channel state information (CSI) is challenging to obtain at the base station (BS) due to the lack of radio frequency (RF) chains at the IRS. Since most of the existing channel estimation methods were developed to acquire the cascaded BS-IRS-user channels, this paper is the first work to study the robust beamforming based on the imperfect cascaded BS-IRS-user channels at the transmitter (CBIUT). Specifically, the transmit power minimization problems are formulated subject to the worst-case rate constraints under the bounded CSI error model, and the rate outage probability constraints under the statistical CSI error model, respectively. After approximating the worst-case rate constraints by using the S-procedure and the rate outage probability constraints by using the Bernstein-type inequality, the reformulated problems can be efficiently solved. Numerical results show that the negative impact of the CBIUT error on the system performance is greater than that of the direct CSI error.

中文翻译：

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具有不完美级联通道的 IRS 辅助 MISO 通信的稳健传输设计框架

智能反射面 (IRS) 最近被认为是一种很有前途的技术，因为它能够重新配置信号传播环境，从而增强无线系统的性能。然而，由于 IRS 缺乏射频 (RF) 链，在基站 (BS) 处获得完美的信道状态信息 (CSI) 具有挑战性。由于大多数现有的信道估计方法都是为了获取级联的 BS-IRS 用户信道而开发的，本文是第一个研究基于发射机（CBIUT）不完美级联 BS-IRS 用户信道的鲁棒波束成形的工作。具体来说，发射功率最小化问题是根据有界 CSI 误差模型下的最坏情况速率约束和统计 CSI 误差模型下的速率中断概率约束来制定的，分别。在使用 S 过程逼近最坏情况速率约束和使用 Bernstein 型不等式逼近速率中断概率约束后，可以有效地解决重新制定的问题。数值结果表明，CBIUT 误差对系统性能的负面影响大于直接 CSI 误差的负面影响。