Figure 4 - uploaded by Laurent Schumacher
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Top view drawing of the antenna array used during the measurement campaign and the postprocessed linear antenna array at the MS.
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The present paper describes the set-up for the measurement of MIMO (Multi-Input-Multi-Output) radio channels as part of the European IST (Information Society Technologies) project METRA (Multi Element Transmit and Receive Antenna). Exploitation of the measurements showed that 0.4λ separation, where λ is the wavelength, between the elements of the a...
Context in source publication
Context 1
... order to provide Direction-of-Arrival (DoA) information, it was decided to use 0.4λ separation between the elements to enable the discrimination of waves coming from the back from waves coming from the front. Figure 4 presents a sketch of the antenna array used. The interleaved solution provides an actual separation of 1.1λ between the elements compared to a traditional linear array. ...
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This document presents a simple framework for Monte-Carlo simulations of a multiple-input-multiple-output (MIMO) radio channel. A stochastic model including the partial correlation between the paths in the MIMO channel, as well as fast fading and time dispersion is proposed. Its implementation in a COSSAP ® primitive model is described. Simulations...
Citations
... A variety of measurements have appeared using such direct measurement platforms [17], [20], [32]- [55]. Results from such campaigns include channel capacity, signal correlation structure (in space, frequency, and time), channel matrix rank, path loss, delay spread, and a host of other quantities. ...
Multiple-input-multiple-output (MIMO) wireless systems use multiple antenna elements at transmit and receive to offer improved capacity over single antenna topologies in multipath channels. In such systems, the antenna properties as well as the multipath channel characteristics play a key role in determining communication performance. This paper reviews recent research findings concerning antennas and propagation in MIMO systems. Issues considered include channel capacity computation, channel measurement and modeling approaches, and the impact of antenna element properties and array configuration on system performance. Throughout the discussion, outstanding research questions in these areas are highlighted.
... On the other hand, the narrowband models assume that the channel has frequency non-selective fading and therefore the channel has the same response over the entire system bandwidth. Wideband MIMO channel models can be found in[20][21][22][23][24][25][26]while[27][28][29][30][31][32][33][34]treat narrowband models. Field Measurements vs. Scatterer Models: to model the MIMO channel, one approach is to measure the MIMO channel responses through field measurements. ...
... Some important characteristics of the MIMO channel can be obtained by investigating the recorded data and the MIMO channel can be modeled to have similar characteristics. Models based on MIMO channel measurements were reported in[20][21][22][23][29][30][31]. An alternative approach is to postulate a model (usually involving distributed scatterers) that attempts to capture the channel characteristics. ...
... Under the European Union IST METRA (Multi Element Transmit Receive Antennas) project, an indoor measurement campaign was carried out in Aalborg, Denmark at a carrier frequency of 2.05 GHz. A stochastic MIMO radio channel model for non-line-of-sight (NLOS) scenarios was proposed based on the power correlation matrix of the MIMO radio channel[20,21]. Let M be the number of transmit antennas and N be the number of receive antennas. In the proposed wideband model, the MIMO channel without noise is expressed as ...
SUMMARY This paper reviews recently published results on multiple input multiple output (MIMO) channel modeling. Both nar- rowband and wideband models are considered. We dis- tinguish between two main approaches to MIMO chan- nel modeling, namely, physically based and non-physically based modeling. The non-physical models primarily rely on the statistical characteristics of the MIMO channels ob- tained from the measured data while the physical models describe the MIMO channel (or its distribution) via some physical parameters. We briefly review different MIMO channel models and discuss their relationships. Some in- teresting aspects will be described in more detail and we note areas where few results are available.
... In [1] and [2] the channel capacity for MIMO systems has been investigated theoretically. Some experimental investigations have also been carried out trying to characterize the MIMO channel and the corresponding capacity, see [3,4,5,6,7]. ...
Herein, results from measurements conducted by the University of
Bristol are presented. The channel characteristics of multiple input
multiple output (MIMO) indoor systems at 5.2 GHz are studied. Our
investigation shows that the envelope of the channel for
non-line-of-sight (NLOS) indoor situations are approximately Rayleigh
distributed and consequently we focus on a statistical description of
the first and second order moments of the narrowband MIMO channel.
Furthermore, it is shown that for NLOS indoor scenarios, the MIMO
channel covariance matrix can be well approximated by a Kronecker
product of the covariance matrices describing the correlation at the
transmitter and receiver side respectively. A statistical narrowband
model for the NLOS indoor MIMO channel based on this covariance
structure is presented
In this paper, the performances of a general MIMO system with arrays at both ends adopting different antenna polarization combinations are studied. Our results show that MIMO systems exploiting the vertically co-polarized antenna arrays at both ends outperform the horizontally co-polarized combination. The adoption of the orthogonal polarization antenna arrays at both ends can achieve parallel transmission and reception pairs at the expense of some subchannel gains, and thus is an efficient way for enhancing channel capacity in a poor-scattering environment. When cross-polarized antenna combination is used at both ends, both isolation and correlation properties are needed to fully describe the system performance whereas a co-polarized antenna combination scheme can be described by correlation property alone.
Radio channels having multipath richness allow multiple-input multiple-output (MIMO) systems to achieve significant capacity gain. Most studies have investigated MIMO channel characteristics by normalizing the signal-to-noise ratio (SNR) out of the channel matrix. However, non-line-of-sight (NLOS) scenarios with rich multipath often experience low SNR. On the other hand, scenarios with line of sight (LOS) usually have high SNR but low multipath richness. The relationship between SNR and multipath richness are studied in this paper using urban environment measurements conducted at 2.53 GHz in downtown Oulu, Finland within a bandwidth of 100 MHz. We investigate a variety of MIMO channel parameters including the small-scale fading characteristics, delay dispersion, and correlation property as well as wideband channel capacity during as the transition from the LOS to the NLOS cases. Also, the polarization dependency on the LOS/NLOS condition is investigated.
Multiple-input and multiple-output (MIMO) channel measurement and analysis are presented based on multiple-input and single-output (MISO) antenna configurations associated with dynamic measurements. The measurement is considered in a time-stationary elliptical scattering in-door propagation scenario, where a special case of the "Kronecker" MIMO channel model is derived and the channel reciprocity for the uplink and downlink is assumed. The cumulative distribution functions (CDF's) of the delay spread and fading envelope, as well as the maximum-to-minimum eigenvalue ratio (MMEVR) are investigated and compared with respect to different antenna spacing and angular spread, respectively. For large angular spread, a wider arrival angle shows that it is not necessary to increase the un-correlated inter-subchannels. These analysis results meet most real MIMO channel statistical property scenarios.
This paper analyzes the MIMO (multi-input-multi-output) channel correlations under different antenna polarization combinations. Measurement results show that the horizontally polarized combination is more correlated than vertically-polarized combination. And in the environment with rich scattering, there is no benefit to using a cross-polarized combination to increase channel capacity. While in the environment without rich scattering, like in open space, the cross-polarized combination is an efficient way for enhancing channel capacity.
In this paper, we present results from measurements conducted by the University of Bristol. We study the channel characteristics of Multiple-Input-Multiple-Output (MIMO) indoor channel at 5.2 GHz. Our investigation shows that the envelope of the channel for non-line-of-sight (NLOS) indoor situations is approximately Rayleigh distributed and consequently we focus on a statistical description of the first and second order moments of the narrowband MIMO channel. Furthermore, it is shown that for NLOS indoor scenarios, the MIMO channel covariance matrix can be well modeled by a Kronecker product of the covariance matrices describing the correlation at the transmitter and the receiver side respectively. A statistical narrowband model for the NLOS indoor MIMO channel based on this covariance structure is presented along with some simulation results. 1.
