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119
A Stochastic Model of the Temporal and Azimuthal Dispersion Seen at the Base Station in Outdoor Propagation Environments
 IEEE Trans. Veh. Technol
, 2000
"... Abstract—A simple statistical model of azimuthal and temporal dispersion in mobile radio channels is proposed. The model includes the probability density function (pdf) of the delay and azimuth of the impinging waves as well as their expected power conditioned on the delay and azimuth. The statis ..."
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Cited by 103 (4 self)
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Abstract—A simple statistical model of azimuthal and temporal dispersion in mobile radio channels is proposed. The model includes the probability density function (pdf) of the delay and azimuth of the impinging waves as well as their expected power conditioned on the delay and azimuth. The statistical properties are extracted from macrocellular measurements conducted in a variety of urban environments. It is found that in typical urban environments the power azimuth spectrum (PAS) is accurately described by a Laplacian function, while a Gaussian pdf matches the azimuth pdf. Moreover, the power delay spectrum (PDS) and the delay pdf are accurately modeled by an exponential decaying function. In bad urban environments, channel dispersion is better characterized by a multicluster model, where the PAS and PDS are modeled as a sum of Laplacian functions and exponential decaying functions, respectively. Index Terms—Antenna arrays, azimuth dispersion, directional channel model, propagation model. I.
Ultrawideband propagation channels  Theory, measurement, and modeling
, 2005
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Cluster Characteristics in a MIMO Indoor Propagation Environment
"... Abstract — Essential parameters of physical, propagationbased MIMO channel models are the fading statistics and the directional spread of multipath clusters. In this paper we determine these parameters in the azimuthofarrival/azimuthofdeparture (AoA/AoD) domain based on comprehensive indoor MIM ..."
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Cited by 28 (0 self)
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Abstract — Essential parameters of physical, propagationbased MIMO channel models are the fading statistics and the directional spread of multipath clusters. In this paper we determine these parameters in the azimuthofarrival/azimuthofdeparture (AoA/AoD) domain based on comprehensive indoor MIMO measurements at 5.2 GHz in a cluttered office environment using the SAGE algorithm for parameter estimation. Due to cluster identification in AoA/AoDdomain we found a greater number of clusters than those reported in previous publications. Regarding the fading statistics of clusters, so far not studied, strong (obstructed)lineofsight clusters show Rician fading, corresponding to few dominant propagation paths, whereas most clusters exhibit Rayleigh fading, corresponding to many paths with approximately equal powers and uncorrelated phases. Rootmeansquare cluster azimuth spreads (CASs) were estimated with a novel method by appropriately restricting the support of the cluster azimuth distribution. We found that the estimated CASs are different when seen from transmitter or receiver, i.e. their ranges are from 2 ◦ to 9 ◦ and from 2 ◦ to 7 ◦ at the transmitter side and the receiver side, respectively. Index Terms — MIMO systems, radio propagation, multipath channels, modeling, clustering methods. I.
Parametric Modelling and Estimation of Distributed Diffuse Scattering Components of Radio Channels
"... Abstract We introduce an extended datamodel for high resolution channel parameter estimation and parametric channel modeling. Other than the wellknown rayoptical based data models which contain only discrete (specular) propagation paths, we additionally introduce distributed diffuse scattering ..."
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Cited by 16 (9 self)
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Abstract We introduce an extended datamodel for high resolution channel parameter estimation and parametric channel modeling. Other than the wellknown rayoptical based data models which contain only discrete (specular) propagation paths, we additionally introduce distributed diffuse scattering components. To this end a simple parametric data model of the diffuse scattering distribution in the delay domain is proposed. Furthermore, we develop an estimator for those model parameters and derive their CramérRao lower bound. Finally we discuss implementation related issues, which arise if the extended channel model is integrated into existing highresolution parameter estimation algorithms (such as ESPRIT, RIMAX, or SAGE) for the estimation of discrete propagation paths. It is demonstrated that also the reliability of highresolution parameter estimation results in channel sounding measurements can be considerably enhanced. I.
Minimumenergy bandlimited predictor with dynamic subspace selection for timevariant flatfading channels
, 2007
"... In this paper, we develop and analyze the basic methodology for minimumenergy (ME) bandlimited prediction of sampled timevariant flatfading channels. This predictor is based on a subspace spanned by timeconcentrated and bandlimited sequences. The timeconcentration of these sequences is matched ..."
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Cited by 15 (11 self)
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In this paper, we develop and analyze the basic methodology for minimumenergy (ME) bandlimited prediction of sampled timevariant flatfading channels. This predictor is based on a subspace spanned by timeconcentrated and bandlimited sequences. The timeconcentration of these sequences is matched to the length of the observation interval and the bandlimitation is determined by the support of the Doppler power spectral density of the fading process. Slepian showed that discrete prolate spheroidal (DPS) sequences can be used to calculate the ME bandlimited continuation of a finite sequence. We utilize this property to perform channel prediction. We generalize the concept of timeconcentrated and bandlimited sequences to a bandlimiting region consisting of disjoint intervals. For a fading process with constant spectrum over its possibly discontiguous support we prove that the ME bandlimited predictor is identical to a reducedrank maximumlikelihood predictor which is a close approximation of a Wiener predictor. In current cellular communication systems the timeselective fading process is highly oversampled. The essential dimension of the subspace spanned by timeconcentrated and bandlimited sequences is in the order of two to five only. The prediction error mainly depends on the support of the Doppler spectrum. We exploit this fact to propose lowcomplexity timevariant flatfading channel predictors using dynamically selected predefined subspaces. The subspace selection is based on a probabilistic bound on the reconstruction error. We compare the performance of the ME bandlimited predictor with a predictor based on complex exponentials. For a prediction horizon of one eights of a wavelength the numerical simulation
A framework for automatic clustering of parametric MIMO channel data including path powers
 in VTC 2006
, 2006
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Detection and tracking of MIMO propagation path parameters using statespace approach
 IEEE Transactions on Signal Processing
, 2009
"... permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Helsinki University of Technology's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or pr ..."
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Cited by 12 (0 self)
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permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Helsinki University of Technology's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubspermissions@ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws
A Gradient Based Method for Maximum Likelihood Channel Parameter Estimation from
 Multidimensional Channel Sounding Measurements,” XXVIIth URSI General Assembly, Maastricht, NL
, 2002
"... We describe a multidimensional maximum likelihood estimator for radio channel parameters. We also derive a data model to describe the complete data, that is virtually applicable to every antenna array geometry. The proposed iterative gradient based algorithm has been developed, since algorithms usin ..."
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Cited by 11 (7 self)
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We describe a multidimensional maximum likelihood estimator for radio channel parameters. We also derive a data model to describe the complete data, that is virtually applicable to every antenna array geometry. The proposed iterative gradient based algorithm has been developed, since algorithms using componentwise updates of the likelihood function shows a slow convergence, if at least two propagation paths with nearly the same parameters exist in the measured radio propagation scenario, that means if superresolution is necessary. The algorithm provides furthermore a variance estimate of the estimated parameters, since the Fisherinformation matrix is calculated throughout the algorithm.
Statistical Characteristics of Indoor Radio Propagation in NLOS Scenarios
 In Nlos Scenarios,” Tech. Rep. COST 259
, 2000
"... This paper presents results of a measurement campaign carried out at a carrier frequency of 24 GHz in indoor nonlineofsight (NLOS) scenarios. The received signal is resolved with respect to the delays, azimuths, elevations, and complex amplitudes of the incident waves. A clustering pattern in bot ..."
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Cited by 9 (0 self)
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This paper presents results of a measurement campaign carried out at a carrier frequency of 24 GHz in indoor nonlineofsight (NLOS) scenarios. The received signal is resolved with respect to the delays, azimuths, elevations, and complex amplitudes of the incident waves. A clustering pattern in both delay and angle of arrival is visible in the data. Clusters correspond to openings such as doorways, and wall transmission. The direct path is not present in the majority of the measured scenarios. Besides a description of the physical propagation effects, we present a global characterization of the investigated radio environment suitable for stochastic channel modeling by means of global power profiles and probability density functions of the channel parameters. 1. Introduction The capacity increase envisaged for future mobile radio systems can only be achieved by exploiting the entire spatialtemporal characteristics of the propagation channel. Consequently, a profound knowledge of the...
Automatic clustering of MIMO channel parameters using the multipath component distance measure
 in WPMC’05
, 2005
"... Abstract — This paper addresses the problem of identifying clusters from MIMO measurement data. Conventionally, visual inspection has been used for the cluster identification, however this approach is impractical for a large amount of measurement data. Moreover, visual methods lack an accurate defin ..."
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Cited by 8 (6 self)
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Abstract — This paper addresses the problem of identifying clusters from MIMO measurement data. Conventionally, visual inspection has been used for the cluster identification, however this approach is impractical for a large amount of measurement data. Moreover, visual methods lack an accurate definition of a “cluster ” itself. We propose to use a previously introduced metric, the multipath component distance (MCD), to calculate the distance between single multipath components (MPCs) estimated by a channel parameter estimator, such as SAGE. The metric scales the different dimensions of the data to be in the interval of [0... 1] and also solves the problem of the angular periodicity. We implemented this metric in the wellknown hierarchical tree clustering algorithm. To assess the performance improvement of the new metric, the clustering algorithm is subsequently applied on synthetic data generated by the 3GPP spatial channel model (SCM) using the MCD, the wellknown euclidean distance metric, and the joint squared euclidean distance as distance functions. Finally we verify the applicability of the metric by results from clustering realworld measurement data from an indoor big hall environment.