Topic
K-distribution
About: K-distribution is a research topic. Over the lifetime, 1281 publications have been published within this topic receiving 51774 citations.
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TL;DR: This distribution can be obtained exactly as the sum of mutual independent Gaussian stochastic processes, because it must represent the simulation of the fading channel; that is, it simulates the signal envelope.
Abstract: We propose an alternative distribution for modelling fading-shadowing wireless channels. This distribution presents certain advantages over the Rayleigh-lognormal distribution and the K distribution and has proved useful in the setting described. We obtain closed-form expressions for the average channel capacity and for the average bit error rate of differential phase-shift keying and of minimum shift keying when the new distribution is used. This distribution can be obtained exactly as the sum of mutual independent Gaussian stochastic processes, because it must represent the simulation of the fading channel; that is, it simulates the signal envelope. Finally, we describe practical applications of this distribution, comparing it with the Rayleigh-lognormal and K distributions.
6 citations
TL;DR: In this article, the scale mixture of matricvariate and matrix variate Kotz-type distributions and the inverse generalised gamma distribution were derived and the generalized Wishart and inverse-Wishart distributions were derived.
Abstract: We have derived the generalised Wishart and inverse-Wishart distributions based on the matrix variate and matricvariate Kotz-type distributions. The scale mixture of matricvariate and matrix variate Kotz-type distributions and the inverse generalised gamma distribution are then proposed. It is shown that the class of distributions termed the family of t -type distributions proposed by Arslan [Arslan, O. (2005). A new class of multivariate distributions: Scale mixture of Kotz-type distributions. Statistics and Probability Letters , 76 , 18–28] is obtained as particular cases of the result given here. We have also derived the compound matricvariate and matrix variate Kotz-type distributions and the inverse generalised Wishart based on the matrix variate and matricvariate Kotz-type distributions. These latter results lead us to propose a different matricvariate version of the family of t -type distributions and others cited in the above-mentioned reference.
6 citations
TL;DR: In this article, a target detection in the presence of Compound-Gaussian (CG) clutter with the Inverse Gaussian (IG) texture and the unknown Power Spectral Density (PSD) was proposed.
Abstract: This paper mainly deals with the problem of target detection in the presence of Compound-Gaussian (CG) clutter with the Inverse Gaussian (IG) texture and the unknown Power Spectral Density (PSD). The traditional CG distributions, in particular the K distribution and the complex multivariate t distribution, are widely used for modeling the real clutter data from the High-Resolution (HR) radars. Recently, the novel CG distribution with the IG texture is described as the IG-CG distribution and validated to provide the better flt with the recorded data of the HR clutter than the mentioned two competitors. Within the IG-CG framework, the detector is flrstly proposed here in terms of the two-step Generalized Likelihood Ratio Test (GLRT) criterion, and the empirical estimation method is resorted to estimate the unknown PSD in order to adapt the realistic scenario. The proposed detector is tested on the real-life HR clutter data, in comparison with the Adaptive Normalized Matched Filter (ANMF) processor, and the detection results illustrate that it outperforms the ANMF.
6 citations
TL;DR: In this article, a simple Markov process model of binary, digitized radar clutter returns is assumed, and probability distributions for the number of hits in n observations are developed for small n with a binary parameter describing the process derived for Rayleigh distributed clutter.
Abstract: A simple Markov process model of binary, digitized radar clutter returns is assumed. Probability distributions for the number of hits in n observations are developed for small n with a binary parameter describing the process derived for Rayleigh distributed clutter. Tables of distributions are included, along with an example to show the effects of correlation on the false-alarm probabilities of a sliding-window detector.
6 citations
TL;DR: In this article, the central theme of limit distributions in a scheme (1) A n d-valued independent random vectors, A i "s are MATRICES (linear bounded operators) on R d and x i's are deterministic R d shift vectors.
Abstract: The central theme of that monograph are limit distributions in a scheme (1) A n d-valued independent random vectors, A i 's are MATRICES (linear bounded operators) on R d and x i 's are deterministic R d shift vectors. If in (1) one assumes that the triangular array A n X k , 1 ≤ k ≤ n, n ≥ 1, is uniformly infinitesimal then limit distributions are called operator-selfdecomposable. This class includes the classical selfdecomposable measures. For independent and identically distributed X i 's limiting laws are called operator-stable measures. Among them we have the classical and well know stable measures.
6 citations