H. Ozcelik

Survey of channel and radio propagation models for wireless MIMO systems

This paper provides an overview of the state-of-the-art radio propagation and channel models for wireless multiple-input multiple-output (MIMO) systems. We distinguish between physical models and analytical models and discuss popular examples from both model types. Physical models focus on the double-directional propagation mechanisms between the location of transmitter and receiver without taking the antenna configuration into account. Analytical models capture physical wave propagation and antenna configuration simultaneously by describing the impulse response (equivalently, the transfer function) between the antenna arrays at both link ends. We also review some MIMO models that are included in current standardization activities for the purpose of reproducible and comparable MIMO system evaluations. Finally, we describe a couple of key features of channels and radio propagation which are not sufficiently included in current MIMO models.

Cluster Characteristics in a MIMO Indoor Propagation Environment

Essential parameters of physical, propagation-based MIMO channel models are the fading statistics and the directional spread of multipath clusters. In this paper we determine these parameters in the azimuth-of-arrival/azimuth-of-departure (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/AoD-domain 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-)line-of-sight 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. Root-mean-square 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 2deg to 9deg and from 2deg to 7deg at the transmitter side and the receiver side, respectively

Correlation matrix distance, a meaningful measure for evaluation of non-stationary MIMO channels

The correlation matrix distance (CMD), an earlier introduced measure for characterization of non-stationary MIMO channels, is analyzed regarding its capability to predict performance degradation in MIMO transmission schemes. For that purpose we consider the performance reduction that a prefiltering MIMO transmission scheme faces due to non-stationary changes of the MIMO channel. We show that changes in the spatial structure of the channel corresponding to high values in the CMD also show up as a significant reduction in performance of the considered MIMO transmission scheme. Such significant changes in the spatial structure of the mobile radio channel are shown to appear also for small movements within an indoor environment. Stationarity can therefore not always be assumed for indoor MIMO radio channels.

Power and complex envelope correlation for modeling measured indoor MIMO channels: a beamforming evaluation

The multivariate complex normal distribution is often employed as a tractable and convenient model for MIMO wireless systems. Several models may result, depending on how the covariance matrix is specified, i.e. power or complex envelope correlation and full or separable (Kronecker) correlation. This paper investigates the differences of the various models by applying a joint transmit/receive beamformer to recent wideband MIMO radio channel measurements at 5.2 GHz. It is found that the Kronecker model, especially for power correlation, significantly alters the joint beamformer spectrum. A multipath clustering model is applied whose parameters are estimated directly from the measured data. The clustering model is able to match capacity pdfs, and resulting simulated joint beamformer spectra look more realistic than those generated with conventional separable correlation functions.

A comparison of measured 8 /spl times/ 8 MIMO systems with a popular stochastic channel model at 5.2 GHz

We compared the average capacities of measured 8 /spl times/ 8 MIMO systems with the capacities calculated from a popular stochastic MIMO model. This model separated the influence of fading from the correlation at transmit (TX) and receive (RX) arrays. By using directional RX antennas and a virtual 20 /spl times/ 10 TX array with omni antennas, the MIMO channel at different RX positions in an outdoor office scenario at 5.2 GHz was measured. For low correlation at the receiver and transmitter the model fits very well. But for high correlation at both receive and transmit side, considerable discrepancy arose. In these cases, we found that the entries in the fading matrices are not independent identically distributed with mean power of unity, as assumed in the model.

Some remarkable properties of diagonally correlated MIMO channels

This paper investigates so-called diagonally correlated multiple input-multiple output (MIMO) channels, which provide higher ergodic capacity than independent and identically distributed (i.i.d.) fading channels. The presented analysis details physical scenarios leading to such channels, some properties of the channel matrix, and an analytical expression for its ergodic capacity.

On the practical use of analytical MIMO channel models

The practical use of so-called analytical models for representing measured and simulated narrowband MIMO channels is discussed with respect to several metrics. Four analytical models are compared (the Kronecker model, the Weichselberger model, the virtual channel representation, and the diagonal-decorrelation model) using several performance metrics. The investigation is based upon indoor experimental results at 5.2 GHz as well as geometry-based statistical propagation models.

MIMO - study propagation first!

Despite many valuable contributions to the theory and practice of MIMO communication systems from various scientific fields, we want to emphasize the outstanding importance of propagation aspects when dealing with MIMO systems. Radio propagation forms the basis for any radio channel including MIMO systems. On one hand, popular mathematical models and the commonly applied statistical assumptions sometimes turn out to neglect the important properties of MIMO radio channels. On the other hand, the detailed knowledge and investigations of MIMO specific phenomena (e.g. pinholes) does not imply the practical relevance. By means of four specific examples, we argue that studying propagation is indispensable in order to stay in touch with the real MIMO channels.

A diffuse multipath spectrum estimation technique for directional channel modeling

A diffuse spectrum estimation method is presented that is suitable for direction finding for channels with diffuse electromagnetic scattering. The diffuse channel may be the result of physical phenomena (e.g., rough-surface scattering) or limited angular and temporal discrimination of the channel probing equipment. The method decomposes the ideal noncoherent spectrum into a sum of power-weighted basis functions. The basis function coefficients are obtained through a linear programming solution. The method is applied to recent radio channel data collected on the Vienna University of Technology campus. Parameters for a path-based model are extracted using the technique. Site-specific spectra and global capacity comparisons indicate the utility of this new method.

Linking reduction in measured MIMO capacity with dominant-wave propagation

The channel capacity of an 8 /spl times/ 8 multiple-input multiple-output (MIMO) system was measured in a rich-scattering office scenario at 5.2 GHz. It was found that there exist remarkable receive positions and directions within a single office, where a strong reduction in MIMO capacity can be observed. Another reduction is due to different transmit array alignment. Investigating the directions-of-departure and direction-of-arrival, it was shown that these effects are related to dominant-wave propagation.