Showing papers on "Complex normal distribution published in 2002"

Modeling the indoor MIMO wireless channel

Abstract: This paper demonstrates the ability of a physically based statistical multipath propagation model to match capacity statistics and pairwise magnitude and phase distributions of measured 4 /spl times/ 4 and 10 /spl times/ 10 narrow-band multiple-input multiple-output data (MIMO) at 2.4 GHz. The model is compared to simpler statistical models based on the multivariate complex normal distribution with either complex envelope or power correlation. The comparison is facilitated by computing channel element covariance matrices for fixed sets of multipath statistics. Multipolarization data is used to demonstrate a simple method for modeling dual-polarization arrays.

Maximum ratio Combining performance with imperfect channel estimates

Abstract: In this paper, we examine the impact of channel estimation errors on Maximum Ratio Combining (MRC) in receive diversity systems, in the presence of co-channel interferers. The channel is modelled as flat Rayleigh fading, slowly varying and spatially independent. It is assumed that the spatial combiner weights are imperfect estimates of the desired user's fading coefficients and complex Gaussian distributed. Closed form expressions for signal to interference plus noise ratio (SINR) distribution and outage probability is obtained. Using these expressions, the effect of channel estimation quality on performance is investigated.

Quadratic forms in complex Gaussian matrices and performance analysis of MIMO systems with co-channel interference

Abstract: We derive new results dealing with the distribution of the largest eigenvalue of certain quadratic forms in complex Gaussian matrices. These results are useful for the performance analysis of optimized multi-input-multi-output (MIMO) systems subject to co-channel interference.

Statistical characterization of the indoor MIMO channel based on LOS/NLOS measurements

Abstract: Measurements taken at the campus of Brigham Young University (BYU) are used to investigate the statistical properties of the indoor MIMO channel. The Rician K parameter is estimated along a path in both LOS and NLOS. These values are related to the received power and the spatial spectrum calculated using the conventional beamformer. Furthermore, statistical tests are applied to investigate if the data belongs to a multivariate normal distribution. It is found that the univariate statistics can be approximated by a complex normal distribution but only small MIMO systems may be approximated as multivariate normally distributed.

Linear MMSE multiuser receivers: MAI conditional weak convergence and network capacity

Abstract: We explore the performance of minimum mean-square error (MMSE) multiuser receivers in wireless systems where the signatures are modeled as random and take values in complex space. First we study the conditional distribution of the output multiple-access interference (MAI) of the MMSE receiver. By appealing to the notion of conditional weak convergence, we find that the conditional distribution of the output MAI, given the received signatures and received powers, converges in probability to a proper complex Gaussian distribution that does not depend on the signatures. This result indicates that, in a large system, the output interference of the MMSE receiver is approximately Gaussian with high probability, and that systems with MMSE receivers are robust to the randomness of the signatures. Building on the Gaussianity of the output interference, we then take the quality of service (QoS) requirements as meeting the signal-to-interference ratio (SIR) constraints and identify the network capacity of single-class systems with random spreading. The network capacity is expressed uniquely in terms of the SIR requirements and received power distributions. Compared to the network capacity corresponding to the optimal signature allocation, we conclude that at the cost of transmission power, the gap between the network capacity corresponding to optimal signatures and that corresponding to random signatures can be made arbitrarily small. Therefore, from the viewpoint of the network capacity, systems with MMSE receivers are robust to the randomness of signatures.

Conditionally gamma- and k-distribution models for SAR ATR

Abstract: Model-based approaches to automatic target recognition (ATR) generally infer the class and pose of objects in imagery by exploiting theoretical models of the formed images. Recently, we have performed an evaluation of several statistical models for synthetic aperture radar (SAR) and have conducted experiments with ATR algorithms derived from these models. In particular, a one-parameter complex Gaussian model, classically used to model diffuse scattering, was shown to deliver higher recognition rates than a one-parameter quarter-power normal model on actual SAR data. However an extended, two-parameter quarter-power model was consistently a better fit to the data than a corresponding two-parameter Gaussian model. In this paper, we apply Rician, gamma, and K distribution models, which are two-parameter extensions of the complex Gaussian and quarter-power normal models, to ATR from SAR magnitude imagery. We consider maximum-likelihood estimation of unknown model parameters and apply the resulting training and testing algorithms to actual SAR data. We show that the K distribution model performs better than the Rician and gamma models for both large and small sample sizes. The one-parameter complex Gaussian model performed slightly better than the K model overall. For small sample sizes, this is likely due to the relative stability in estimating only one model parameter. For large sample sizes this is likely due to a lack of persistence in specular reflections over the large angular intervals required to obtain large samples.

Complex Gaussian functions for four-particle systems

Abstract: A new type of basis function is suggested for precision variational calculations of many-particle atomic-molecular systems—the Gaussian functions with complex exponential parameters in the form of combinations of exponential-trigonometric functions of the squared interparticle separations. With these basis functions, all required many-particle integrals are evaluated explicitly. The method is applied to totally nonadiabatic calculations of ten four-particle molecules and mesomolecules ranging from the tritium molecule t+t+e−e− to the positronium molecule e+e+e−e−. The dissociation energies of these systems calculated by using 20 complex basis functions coincide with the exact values to within 1%; therefore, their inaccuracy is several times smaller than the inaccuracy of calculations with the basis sets of ordinary real Gaussian functions. This increase in accuracy is attained due to a more correct description of the vibrational part of wave functions of molecular systems by using oscillating complex Gaussian functions as compared to their nodeless real counterparts.

Third order speckle intensity frequency correlations for random media characterization

Abstract: Summary form only given Techniques for characterizing random media are motivated in part by recent interest in important applications such as optical imaging in biological tissue We show for the first time that the third order frequency correlation of measured speckle intensities using coherent light enables the temporal response of a random medium to be obtained In particular, we present experimental results for a random medium in the weak scattering limit and the diffusive regime, where the field statistics are circular complex Gaussian

Third order speckle intensity frequency correlations for random media characterization

Abstract: Summary from only given. Techniques for characterizing random media are motivated in part by recent interest in important applications such as optical imaging in biological tissue. We show for the first time that the third order frequency correlation of measured speckle intensities using coherent light enables the temporal response of a random medium to be obtained. In particular, we present experimental results for a random medium in the weak scattering limit and the diffusive regime, where the field statistics are circular complex Gaussian.