Showing papers on "Complex normal distribution published in 2022"
TL;DR: An autoregressive (AR) model is developed to describe the channel in the frequency domain with few parameters, and the absolute value and phase of each pole satisfied the Weibull and gamma distributions and the variance obeyed a lognormal distribution.
7 citations
23 May 2022
TL;DR: A robust and sparse Direction of Arrival (DOA) estimation framework based on the assumption that the array data has a centered (zero-mean) complex elliptically symmetric complex Gaussian distribution with finite second-order moments is derived.
Abstract: Recent investigations indicate that Sparse Bayesian Learning (SBL) is lacking in robustness. We derive a robust and sparse Direction of Arrival (DOA) estimation framework based on the assumption that the array data has a centered (zero-mean) complex elliptically symmetric (ES) distribution with finite second-order moments. In the derivation, the loss function can be quite general. We consider three specific choices: the ML-loss for the circularly symmetric complex Gaussian distribution, the ML-loss for the complex multivariate t-distribution (MVT) with ν degrees of freedom, and the loss for Huber’s M-estimator. For Gaussian loss, the method reduces to the classic SBL method. The root mean square DOA performance of the derived estimators is discussed for Gaussian, MVT, and ϵ- contaminated noise. The robust SBL estimators perform well for all cases and nearly identical with classical SBL for Gaussian noise.
3 citations
TL;DR: Wei et al. as discussed by the authors reported partial results related to the Gaussian product inequality conjecture for the joint distribution of traces of Wishart matrices and showed that a Kronecker product form of the GPI holds for diagonal blocks of any Wishart distribution.
3 citations
1 citations
11 Jul 2022
TL;DR: In this paper , the performance of the estimator in case of double IRS assisted single-user single input single output (SISO) communication system is evaluated under Bayesian setting.
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.