Multi-Link MIMO Channel Modeling Using Geometry-Based Approach

Poutanen, Juri; Tufvesson, Fredrik; Haneda, Katsuyuki; Kolmonen, Veli-Matti; Vainikainen, P.

doi:10.1109/tap.2011.2122296

Cited by 49 publications

(17 citation statements)

References 12 publications

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“…Geometry-based models introduced in Sect. 3.1.2 are vital bases for including the inter-link correlation since they can consider the physical scatteres that are common to multiple links and can control the inter-link correlation, as demonstrated at lower frequency bands [183]. However, parameterization of the model is presently lacking because of very few channel data that allow for it and rather involved parameterization procedure.…”

Section: Multi-user and Multi-site Channel Modelmentioning

confidence: 99%

Channel Models and Beamforming at Millimeter-Wave Frequency Bands

Haneda

2015

IEICE Trans. Commun.

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SUMMARYMillimeter-wave (mm-wave) radio is attracting attention as one of the key enabling physical layer technologies for the fifthgeneration (5G) mobile access and backhaul. This paper aims at clarifying possible roles of mm-wave radio in the 5G development and performing a comprehensive literature survey on mm-wave radio channel modeling essential for the feasibility study. Emphasis in the literature survey is laid on grasping the typical behavior of mm-wave channels, identifying missing features in the presently available channel models for the design and evaluation of the mm-wave radio links within the 5G context, and exemplifying different channel modeling activities through analyses performed in the authors' group. As a key technological element of the mm-wave radios, reduced complexity beamforming is also addressed. Design criteria of the beamforming are developed based on the spatial multipath characteristics of measured indoor mm-wave channels.

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Section: Multi-user and Multi-site Channel Modelmentioning

confidence: 99%

Channel Models and Beamforming at Millimeter-Wave Frequency Bands

Haneda

2015

IEICE Trans. Commun.

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“…In other cases, spatial correlation is also introduced by common scatterers (walls in street canyon, high buildings in city center, etc.) seen by different users even when they are not well co-located [6], [7]. Fig.…”

Section: Mutual Orthogonalitymentioning

confidence: 94%

On the Mutual Orthogonality of Millimeter-Wave Massive MIMO Channels

Nguyen

Haneda

Järveläinen

et al. 2015

2015 IEEE 81st Vehicular Technology Conference (VTC Spring)

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Mutual orthogonal user channels in multiuser (MU)multiple-input multiple-output (MIMO) systems are desirable and can be approximately obtained under independent and identically distributed (i.i.d.) Rayleigh fading assumption with a very large number of base station antennas. However, it has been shown that at millimeter-wave (mmW) frequencies, this assumption is not valid due to the limited number of multipath components and spatial channel correlation. In this paper, we examine the mutual orthogonality of a realistic 60-GHz outdoor propagation channel with practical large antenna arrays, and determine the factors deciding it based on the channel data generated by means of deterministic field prediction. The results obtained reveal relationships between mutual orthogonality, inter-user distance, number of active users, transmit array dimensions, and downlink system capacity at 60-GHz band, which are useful for designing future mmW massive MU-MIMO systems.

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“…Here both of them is stored as the known data after the pre-processing calculations. The EADF are stored in a 12 LL  matrix for the reference model (6), where 12 27 LL  [19]. According to Table 1, the number of effective values of ERDF marked at the top of the bar ensures a small reconstruction error.…”

Section: The Proposed Model With Effective Response Distribution Funcmentioning

confidence: 99%

“…We focus on the physical models because they are more accurate and have a wide spectrum for application. The geometry-based model is a kind of physical model that takes the geometry of a channel into account [11][12]. The double directional channel is a classical geometry-based model, where each path is described by parameters, such as the propagation delay, direction of arrival (DOA) and direction of departure (DOD) [13].…”

Section: Introductionmentioning

confidence: 99%

An Efficient Response Distribution Function for 3D MIMO Channel Modeling from a Scatterer View

Sheng¹,

Wang

et al. 2016

IJFGCN

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A Radio Environment Map (REM) maps its geolocation information to the propagation characteristics as complementary information for an adaptive communication of cognitive radio (CR). In this paper we propose a novel theoretical three dimension (3D) Multiple Input Multiple Output (MIMO) channel model. The proposed model parameterizes the geolocation information of interacting obstacles referred as scatterers. An efficient response distribution function (ERDF) is developed to interpolate the array response for an arbitrary scatterer location. It is shown that the mutual information of the proposed model is consistent with a conventional geometry-based model with the lower simulation time. It allows us to generate channels with all possible scatterer distribution on the surface of a building effectively.

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Multi-Link MIMO Channel Modeling Using Geometry-Based Approach

Cited by 49 publications

References 12 publications

Channel Models and Beamforming at Millimeter-Wave Frequency Bands

Channel Models and Beamforming at Millimeter-Wave Frequency Bands

On the Mutual Orthogonality of Millimeter-Wave Massive MIMO Channels

An Efficient Response Distribution Function for 3D MIMO Channel Modeling from a Scatterer View

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