Spatial separation of multi-user MIMO channels

Czink, Nicolai; Bandemer, Bernd; Vazquez-Vilar, Gonzalo; Jalloul, Louay M. A.; Oestges, Claude; Paulraj, A.

doi:10.1109/pimrc.2009.5450309

Cited by 42 publications

(26 citation statements)

References 6 publications

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“…The set of channel measurement conducted at Stanford University has been chosen, and specifically it corresponds to the "I2I stationary" scenario measurement therein [22].…”

Section: The Mr-fdpf Modelmentioning

confidence: 99%

Generation of 2D correlated random shadowing based on the deterministic MR-FDPF model

Luo

Villemaud

Gorce

2015

J Wireless Com Network

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In modern mobile telecommunications, shadow fading has to be modeled by a two-dimensional (2D) correlated random variable since shadow fading may present both cross-correlation and spatial correlation due to the presence of similar obstacles during the propagation. In this paper, 2D correlated random shadowing is generated based on the multi-resolution frequency domain ParFlow (MR-FDPF) model. The MR-FDPF model is a 2D deterministic radio propagation model, so a 2D deterministic shadowing can be firstly extracted from it. Then, a 2D correlated random shadowing can be generated by considering the extracted 2D deterministic shadowing to be a realization of it. Moreover, based on the generated 2D correlated random shadowing, a complete 2D semi-deterministic path loss model can be proposed. The proposed methodology of this paper can be implemented into system-level simulators where it will be very useful due to its ability to generate realistic shadow fading.

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“…The set of channel measurement conducted at Stanford University has been chosen, and specifically it corresponds to the "I2I stationary" scenario measurement therein [22].…”

Section: The Mr-fdpf Modelmentioning

confidence: 99%

Generation of 2D correlated random shadowing based on the deterministic MR-FDPF model

Luo

Villemaud

Gorce

2015

J Wireless Com Network

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“…Two links may also have very different inter-link correlation even if they are in the same environment (e.g. in the same room) [9].…”

Section: A Motivationmentioning

confidence: 99%

Multi-Link MIMO Channel Modeling Using Geometry-Based Approach

Poutanen

Tufvesson

Haneda

et al. 2012

IEEE Trans. Antennas Propagat.

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Abstract-This paper presents an approach to extend geometry-based stochastic channel models (GSCMs) to support multi-link simulations by applying the concept of common clusters. The idea of the proposed approach is to control the correlation between different links, inter-link correlation, by adjusting the amount of power simultaneously propagating via the same clusters in the different links. A multi-link GSCM is proposed, and the effects that the common clusters have on interlink correlation and on sum rate capacity are investigated based on simulations. In addition, the behavior of common clusters is analyzed based on dual-link channel measurements. Finally, comparison between simulations and measurements is done in order to indicate the validity of the proposed multi-link GSCM.

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“…To quantify it, we use (i) raytracing simulations and (ii) data from a recently conducted radio measurement campaign, using the RUSK Stanford multi-antenna radio channel sounder with a center frequency of 2.45 GHz and bandwidth of 240 MHz [14].…”

Section: Contributionmentioning

confidence: 99%

“…More details on the full campaign can be found in [14]. In this appendix, we briefly summarize the most important features of the measurement setup.…”

Section: A2 Radio Channel Measurementsmentioning

confidence: 99%

Correlation-based radio localization in an indoor environment

Callaghan

Czink

Mani

et al. 2011

J Wireless Com Network

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We investigate the feasibility of using correlation-based methods for estimating the spatial location of distributed receiving nodes in an indoor environment. Our algorithms do not assume any knowledge regarding the transmitter locations or the transmitted signal, but do assume that there are ambient signal sources whose location and properties are, however, not known. The motivation for this kind of node localization is to avoid interaction between nodes. It is most useful in non-line-of-sight propagation environments, where there is a lot of scattering. Correlation-based node localization is able to exploit an abundance of bandwidth of ambient signals, as well as the features of the scattering environment. The key idea is to compute pairwise cross correlations of the signals received at the nodes and use them to estimate the travel time between these nodes. By doing this for all pairs of receivers, we can construct an approximate map of their location using multidimensional scaling methods. We test this localization algorithm in a cubicle-style office environment based on both ray-tracing simulations, and measurement data from a radio measurement campaign using the Stanford broadband channel sounder. Contrary to what is seen in other applications of cross-correlation methods, the strongly scattering nature of the indoor environment complicates distance estimation. However, using statistical methods, the rich multipath environment can be turned partially into an advantage by enhancing ambient signal diversity and therefore making distance estimation more robust. The main result is that with our correlation-based statistical estimation procedure applied to the real data, assisted by multidimensional scaling, we were able to compute spatial antenna locations with an average error of about 2 m and pairwise distance estimates with an average error of 1.84 m. The theoretical resolution limit for the distance estimates is 1.25 m.

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Spatial separation of multi-user MIMO channels

Cited by 42 publications

References 6 publications

Generation of 2D correlated random shadowing based on the deterministic MR-FDPF model

Generation of 2D correlated random shadowing based on the deterministic MR-FDPF model

Multi-Link MIMO Channel Modeling Using Geometry-Based Approach

Correlation-based radio localization in an indoor environment

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