Channel estimation for double IRS assisted broadband single-user SISO communication

Vishnu Karthikeya Gorty
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引用次数: 2

Abstract

In this paper, two Intelligent reflecting surfaces (double IRS) assisted single-user single input single output (SISO) communication system is considered. The cascaded channels (mobile user (MU) $\rightarrow$ IRS$- 1 \rightarrow$ base station (BS), MU $\rightarrow$ IRS$- 2 \rightarrow$ BS and MU $\rightarrow$ IRS$- 1 \rightarrow$ IRS$- 2 \rightarrow$ BS channels) are estimated under Bayesian setting. Here, the goal is to evaluate the performance of the estimator in case of MU $\rightarrow$ IRS$- 1 \rightarrow$ BS and MU $\rightarrow$ IRS$- 2 \rightarrow$ BS channel links using Bayesian Cramér-Rao lower bound (CRLB). Without the knowledge of closed form pdf of inner product of circularly symmetric complex Gaussian (CSCG) random vectors, we cannot obtain the fisher information. Hence, by numerical computation we obtain the Bayesian CRLB. In the simulation results, we show that we can approximate the pdf of the inner product of CSCG random vectors by a Rayleigh distribution by increasing the number of elements on the IRS, which is analogous to Central Limit Theorem (CLT). Also, the results convey that the mean squared error (MSE) almost matches with the Bayesian CRLB.
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双IRS辅助宽带单用户SISO通信的信道估计
研究了双智能反射面(双IRS)辅助单用户单输入单输出(SISO)通信系统。在贝叶斯设置下估计了级联信道(移动用户(MU) $\rightarrow$ IRS$- 1 \rightarrow$基站(BS)、MU $\rightarrow$ IRS$- 2 \rightarrow$ BS和MU $\rightarrow$ IRS$- 1 \rightarrow$ IRS$- 2 \rightarrow$ BS信道)。在这里,目标是使用贝叶斯cram - rao下界(CRLB)来评估MU $\rightarrow$ IRS$- 1 \rightarrow$ BS和MU $\rightarrow$ IRS$- 2 \rightarrow$ BS信道链接情况下估计器的性能。如果不知道圆对称复高斯(CSCG)随机向量内积的封闭形式pdf,就无法获得fisher信息。因此,通过数值计算,我们得到了贝叶斯CRLB。仿真结果表明,通过增加IRS上的元素个数,可以近似地得到CSCG随机向量内积的pdf,这与中心极限定理(CLT)类似。此外,结果表明,均方误差(MSE)与贝叶斯CRLB基本匹配。
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