Sharif Digital Repository

In this paper, we investigate the effect of applying an exponential window on the limiting spectral distribution (l.s.d.) of the exponentially windowed sample covariance matrix (SCM) of complex array data. We use recent advances in random matrix theory which describe the distribution of eigenvalues of the doubly correlated Wishart matrices. We derive an explicit expression for the l.s.d. of the noise-only data. Simulations are performed to support our theoretical claims  

This paper presents a scheme to enumerate the incident waves impinging on a high dimensional uniform linear array using relatively few samples. The approach is based on Minimum Description Length (MDL) criteria and statistical properties of eigenvalues of the Sample Covariance Matrix (SCM). We assume that several models, with each model representing a certain number of sources, will compete and MDL criterion will select the best model with the minimum model complexity and maximum model decision. Statistics of noise eigenvalue of SCM can be approximated by the distributional properties of the eigenvalues given by Marcenko-Pastur distribution in the signal-free SCM. In this paper we use random... 

In this paper, we consider an exponentially windowed sample covariance matrix (EWSCM) and propose an improved estimator for its eigenvalues. We use new advances in random matrix theory, which describe the limiting spectral distribution of the large dimensional doubly correlated Wishart matrices to find the support and distribution of the eigenvalues of the EWSCM. We then employ the complex integration and residue theorem to design an estimator for the eigenvalues, which satisfies the cluster separability condition, assuming that the eigenvalue multiplicities are known. We show that the proposed estimator is consistent in the asymptotic regime and has good performance in finite sample size... 

In this letter, we surpass the jamming effect and also estimate the jamming channel state information by using the Kalman filtering approach. Furthermore, we design a closed-form beamforming weight for maximizing the achievable rate subject to the condition that the total relays power transmission would be below a predefined threshold level, which is formulated as a quadratically constrained quadratic program. Simulation results show the efficient performance of the proposed method for different destruction powers of the jammer by achieving the Cramér-Rao lower bound. © 1997-2012 IEEE  

In this letter, we surpass the jamming effect and also estimate the jamming channel state information by using Kalman filtering (KF) approach. Furthermore, we design a closed-form beamforming weight for maximizing the achievable rate subject to the condition that the total relays power transmission would be below a predefined threshold level, which is formulated as a Quadratically Constrained Quadratic Program (QCQP). Simulation results show efficient performance of the proposed method for different destruction powers of jammer by achieving the Cramer Rao Lower Bound (CRLB). IEEE  

Signal direction-of-arrival (DOA) estimation using an array of sensors has been the subject of intensive research and development during the last two decades. Efforts have been directed to both, better solutions for the general data model and to develop more realistic models. So far, many authors have assumed the data to be independent and identically distributed (i.i.d.) samples of a multivariate statistical model. Although this assumption reduces the complexity of the model, it may not be true in certain situations where signals show temporal correlation. Some results are available on the temporally correlated signal model in the literature. The temporally correlated stochastic Cramér-Rao...