Multi-frequency interferometry (MFI) is well known as an accurate phase-based measurement scheme. The paper reveals the inherent relationship of the unambiguous measurement range (UMR), the outlier probability, the MSE performance with the frequency pattern in MFI system, and then provides the corresponding criterion for choosing the frequency pattern. We point out that the theoretical rigorous...

This work presents joint interference suppression and power allocation algorithms for DS-CDMA networks with multiple hops and decode-and-forward (DF) protocols. A scheme for joint allocation of power levels across the relays subject to group-based power constraints and the design of linear receivers for interference suppression is proposed. A constrained minimum mean-squared error (MMSE) design...

Pair-wise Markov random fields (MRF) are considered for application to the development of low complexity, iterative MIMO detection. Specifically, we consider two types of MRF, namely, the fully-connected and ring-type. For the edge potentials, we use the bivariate Gaussian function obtained by marginalizing the posterior joint probability density under the Gaussian assumption. Since the corresp...

Abstract We consider generalized linear models in regimes where the number of nonzero components signal and accessible data points are sublinear with respect to size signal. prove a variational formula for asymptotic mutual information per sample when system grows infinity. This result allows us derive an expression minimum mean-square error (MMSE) Bayesian estimator entries have discrete distr...

Abstract—We investigate a stochastic signal-processing framework for signals with sparse derivatives, where the samples of a Lévy process are corrupted by noise. The proposed signal model covers the well-known Brownian motion and piecewise-constant Poisson process; moreover, the Lévy family also contains other interesting members exhibiting heavy-tail statistics that fulfill the requirements of...

Image up-sampling in the discrete cosine transform (DCT) domain is a challenging problem because DCT coefficients are de-correlated, such that it is nontrivial to estimate directly high-frequency DCT coefficients from observed low-frequency DCT coefficients. In the literature, DCT-based up-sampling algorithms usually pad zeros as high-frequency DCT coefficients or estimate such coefficients wit...

Single Image Super-Resolution algorithms based on patches have been noticed and widely used over the past decade. Recently, generalized Gaussian mixture models (GGMMs) shown to be a suitable tool for many image processing problems because of flexible shape parameter. In this work, we introduce supervised GGMM-based approach super-resolution two- three-dimensional images, in particular materials...

For a zero mean, proper, complex random vector x, the Hermitian covariance Exx is a complete second-order characterization. However, if the vector x is improper, it is correlated with its complex conjugate, meaning Exx 6= 0. This improper or complementary covariance must be accounted for in a complete second-order characterization. The improper covariance has been exploited for widely linear (W...

SORTD (Space Orthogonal-Resource Transmit Diversity) has already become a better way of transmit diversity for PUCCH format 3 in LTE-A [1]. SORTD technology lies in the characteristic that each antenna port transmits signal by using different cyclic shift [2] to make orthogonal each other. Using the SORTD’s feature of incoherence in different antennas, this paper proposes a special form of sign...

This paper presents a codebook-based speech enhancement algorithm by using Markov process and speech-presence probability (SPP). The Markov process is utilized to model the correlation between the adjacent code-vectors in the codebook for optimizing Bayesian minimum mean squared error (MMSE) estimator. Then the proposed estimator is used to estimate spectral shapes and gains of speech and noise...