This paper proposes orthogonal Discrete Frequency Coding Space Time Waveforms (DFCSTW) for Multiple Input and Multiple Output (MIMO) radar detection in compound Gaussian clutter. The proposed orthogonal waveforms are designed considering the position and angle of the transmitting antenna when viewed from origin. These orthogonally optimized show good resolution in spikier clutter with Generaliz...

Bit-interleaved coded modulation with iterative detection for MIMO systems demands an efficient APP detector that delivers soft information about the coded bits. The list-sequential detector is a reduced-complexity approximation to an exhaustive APP detector. It uses a tree search employing the stack algorithm to find dominant terms of the log-likelihood ratio. The commonly used symbol-by-symbo...

This paper develops a newmultiuser detector based on a network of kalman filters (NKF) dealing withmultiple-access interference (MAI), intersymbol interference (ISI), and an impulsive observation noise. The two proposed schemes are based on the modeling of the DS-CDMA system by a discrete-time linear system that has non-Gaussian state and measurement noises. By approximating the non-Gaussian de...

We consider the performance of blind maximum likelihood sequence detection (MLSD) when the recursive leastsquares (RLS) algorithm is used to update channel estimates. We employ asymptotic efficiency analysis to characterize the performance of the detector as the signal-to-noise ratio (SNR) approaches infinity. Asymptotic efficiency analysis allows us to quantify the loss in performance due to t...

The aim of this study is to analyze the influence of neglecting K distributed clutter texture on wideband radar distributed targets detection. At first, the texture and the speckle of K clutter are researched and the Probability Density Function (PDF) of K clutter and its texture are derived, then the optimal detector by Neyman-Pearson (NP) is proposed, by contrast, another detector-Suboptimum ...

Energy detection is widely used in cognitive radio due to its low complexity. One fundamental challenge is that its performance degrades in the presence of noise uncertainty, which inevitably occurs in practical implementations. In this work, three novel detectors based on uniformly distributed noise uncertainty as the worst-case scenario are proposed. Numerical results show that the new detect...

This approach has several advantages: (1) there is no need to estimate the variance/covariance at all, which may become prohibitively complicated for other procedures that requires the estimation of such. (2) When inverting the tests to obtain confidence regions/intervals, this procedure inherits all the good properties of a likelihood ratio test. (3) Free software implementation of the test is...

A new approach of parameterization is proposed to construct a general goodnessof-fit test. It can not only generate traditional tests (including the Kolmogorov–Smirnov, Cramér– von Mises and Anderson–Darling tests) but also produce new types of omnibus tests, which are generally much more powerful than the old ones.

In regression analysis of count data, independent variables are often modeled by their linear effects under the assumption of log-linearity. In reality, the validity of such an assumption is rarely tested, and its use is at times unjustifiable. A lack-of-fit test is proposed for the adequacy of a postulated functional form of an independent variable within the framework of semiparametric Poisso...

In this paper, we study the detection boundary for minimax hypothesis testing in the context of high-dimensional, sparse binary regression models. Motivated by genetic sequencing association studies for rare variant effects, we investigate the complexity of the hypothesis testing problem when the design matrix is sparse. We observe a new phenomenon in the behavior of detection boundary which do...