The COST 2100 MIMO channel model

Liu, Lingfeng; Oestges, Claude; Poutanen, Juho; Haneda, Katsuyuki; Vainikainen, P.; Quitin, François; Tufvesson, Fredrik; Doncker, P. De

doi:10.1109/mwc.2012.6393523

Cited by 585 publications

(360 citation statements)

References 6 publications

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“…Different from parameterizing the shape of power spectrum, this model further elaborates attributes of multipath plane waves to physical but imaginary distribution of electromagnetic field scatterers. Creation of the scatterer distribution is made either on an imaginary map, e.g., [99], where each scatterer is characterized by the three-dimensional coordinate, or with angles of departure and arrival and delay of each scatterer seen from the Tx and Rx antennas, e.g., [100]. These approaches have similarities to the site-specific modeling detailed in Sect.…”

Section: Power Delay Profilesmentioning

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: Power Delay Profilesmentioning

confidence: 99%

Channel Models and Beamforming at Millimeter-Wave Frequency Bands

Haneda

2015

IEICE Trans. Commun.

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“…However, due to the fact that the non-stationary spherical wavefront critically affects both the receiver design and its performance, it is important to model this property of the LS-MIMO channel. So, the COST 2100 channel model of [38] has been extended to include the effect of the wavefront's non-stationary [37]; When considering both the non-stationary wavefront propagation phenomenon and the spherical nature of the waveform, an elliptical GBSM is proposed for LS-MIMO systems based on a linear AA in [39], [40]. Also, the birthdeath process of clusters appearing and disappearing is discussed in [39] for the sake of characterizing its nonstationary nature.…”

Section: ) Gbsmmentioning

confidence: 99%

Survey of Large-Scale MIMO Systems

Zheng

Zhao

Mei

et al. 2015

IEEE Commun. Surv. Tutorials

286

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Abstract-The escalating teletraffic growth imposed by the proliferation of smartphones and tablet computers outstrips the capacity increase of wireless communications networks. Furthermore, it results in substantially increased carbon dioxide emissions. As a powerful countermeasure, in the case of full-rank channel matrices, MIMO techniques are potentially capable of linearly increasing the capacity or decreasing the transmit power upon commensurately increasing the number of antennas. Hence, the recent concept of large-scale MIMO (LS-MIMO) systems has attracted substantial research attention and been regarded as a promising technique for next-generation wireless communications networks. Therefore, this paper surveys the state of the art of LS-MIMO systems. First, we discuss the measurement and modeling of LS-MIMO channels. Then, some typical application scenarios are classified and analyzed. Key techniques of both the physical and network layers are also detailed. Finally, we conclude with a range of challenges and future research topics.Index Terms-Large-scale MIMO, 3-D MIMO, channel modeling, physical layer, networking.

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“…Geometrybased stochastic channel models, such as the WINNER spatial channel models [3], IMT-Advanced models [4], and COST2100 multiple-input multiple-output (MIMO) models [5], have been proposed in various standards and widely used to generate single-and multi-link channel realizations at the carrier frequency up to 6 GHz with a bandwidth up to 100 MHz.…”

Section: Introductionmentioning

confidence: 99%

Parameter estimation using the sliding-correlator’s output for wideband propagation channels

Yin

Cen

Kim

et al. 2015

J Wireless Com Network

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In this contribution, a high-resolution parameter estimation algorithm is derived based on the Space-Alternating Generalized Expectation-maximization (SAGE) principle for extracting multipath parameters from the output of sliding correlator (SC). The SC allows calculating channel impulse responses with a sampling rate less than that required by Nyquist criterion, and hence is widely used in real-time wideband (e.g., >500 MHz) channel sounding for the fifth generation wireless communication scenarios. However, since the sounding signal needs to be sent repetitively, the SC-based solution is unacceptable for time-variant channel measurements. The algorithm proposed here estimates multipath parameters by using a parametric model of both low-and high-frequency components of the SC's output. The latter was considered as distortions and discarded in the conventional SC-based channel sounding. The new algorithm allows estimating path parameters with less repetitions of transmitting the sounding signal and still exhibits higher estimation accuracy than the conventional method. Simulations are conducted and illustrate the root mean square estimation errors and the resolution capability of the proposed algorithm with respect to the bandwidth and the length of the SC's output. These studies pave the way for measuring time-variant wideband propagation channels using SC-based solutions.

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The COST 2100 MIMO channel model

Cited by 585 publications

References 6 publications

Channel Models and Beamforming at Millimeter-Wave Frequency Bands

Channel Models and Beamforming at Millimeter-Wave Frequency Bands

Survey of Large-Scale MIMO Systems

Parameter estimation using the sliding-correlator’s output for wideband propagation channels

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