Development of multi-link geometry-based stochastic channel models

Haneda, Katsuyuki; Poutanen, Juho; Tuvfesson, Fredrik; Liu, Lingfeng; Kolmonen, Veli-Matti; Vainikainen, P.; Oestges, Claude

doi:10.1109/lapc.2011.6114003

Cited by 8 publications

(14 citation statements)

References 21 publications

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“…In general, the comparison between the measured LSPs and synthesized LSPs from the model depends on the qualities of channel estimation and model parameterization. The COST 2100 model validation is extensively covered in [14]. In the following, we focus on one metric representative of multi-link scenarios.…”

Section: Model Validationmentioning

confidence: 99%

“…In the following, we focus on one metric representative of multi-link scenarios. Figure 6 presents a comparison between measurements and corresponding model simulations on the inter-link correlation in a dual-BS single-MS communication scenario [14]. The measurements were performed in an indoor corridor environment at 5.3 GHz [9].…”

Section: Model Validationmentioning

confidence: 99%

“…Verticallypolarized planar dipole antenna arrays were considered at the BSs and MS. Detailed settings of the measurements and the simulations can be found in [14]. Because of the dominant waveguiding propagation in the corridor, the measurements show significant inter-link correlation between two BSs located at different wings of the same building.…”

Section: Model Validationmentioning

confidence: 99%

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The COST 2100 MIMO channel model

Liu

Oestges

Poutanen

et al. 2012

IEEE Wireless Commun.

Self Cite

586

324

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The COST 2100 channel model is a geometry-based stochastic channel model (GSCM) that can reproduce the stochastic properties of multi-link Multiple-Input Mulitple-Output (MIMO) channels over time, frequency and space. By contrast to other popular GSCMs, the COST 2100 approach is generic and flexible, making it suitable to model multiuser or distributed MIMO scenarios. In this paper a concise overview of the COST 2100 channel model is presented. Main concepts are described, together with useful implementation guidelines. Recent developments, including dense multipath components, polarization and multi-link aspects are also discussed.

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Section: Model Validationmentioning

confidence: 99%

Section: Model Validationmentioning

confidence: 99%

Section: Model Validationmentioning

confidence: 99%

See 1 more Smart Citation

The COST 2100 MIMO channel model

Liu

Oestges

Poutanen

et al. 2012

IEEE Wireless Commun.

Self Cite

586

324

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show abstract

“…sequences to un-shareable as well as carriers, by following that the priority of a shareable carrier is lower than that of un-shareable one. In this way, carriers of better quality will be selected and meanwhile the service quality can be also ensured, and thus improving the availability of baseband resource and access success [13].…”

Section: Quence Of Carrier Priorities In Carrier Attribute Schemementioning

confidence: 99%

An Improved DCA and Channel Modelling Algorithm Based on Carrier Priority in LTE/LTE-A

Fereidountabar¹

2013

AJNC

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Dynamic Channel Allocation (DCA) technology is an effective ways to solve the contradiction between limited spectrum resources and increasing user demand in TD-SCDMA system. Aiming at the limitation of conventional DCA algorithm, an improved dynamic channel allocation algorithm based on carrier priority is proposed in this paper to solve tidal phenomenon caused by regional traffic migration and shows channel model. The simulation results show that the proposed algorithm can effectively increase resource utilization and improve access success rate with less changing in channel model.

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“…Many measurements have shown that scatterer points tend to occur in clusters, a fact that is reflected in current standardized GSCM models such as the COST 2100 channel model [3] [4]. Detecting and characterizing (geometrical) clusters of scatterers is thus a fundamental task in channel modeling especially for multi-link channel modelling.…”

Section: Introductionmentioning

confidence: 99%

Geometrical Cluster-Based Scatterer Detection Method with the Movement of Mobile Terminal

Luan

Molisch

Xiao

et al. 2015

2015 IEEE 81st Vehicular Technology Conference (VTC Spring)

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When a mobile station moves along a trajectory, it will see different parts of the same scatterers or scatterer groups during its movement. In this paper, we present a new method to identify such physical clusters of scatterers, and the corresponding groups of multipath components (MPCs) interacting with those clusters, from measurements of channel impulse responses. The method is based on identifying MPCs that have similar long-term properties -in the sense that they "effectively interact with" the same physical clusters, The method consists of four steps: (1) estimate the delays, the DOAs and the amplitudes of the MPCs in each time snapshot; (2) track the MPCs in the time-delay domain; (3) localize all the scattering points in a 2-D Cartesian coordinate system and cluster them on a map with a traditional Kmeans clustering algorithm; (4) merge the scattering points of different MPCs into physical clusters.The method is evaluated using both synthetic data and real measurement data from a suburban area. In the latter case, the locations and the sizes of the interacting objects identified from the measurements show excellent agreement with the location of physical objects in the environment such as pillars and buildings

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Development of multi-link geometry-based stochastic channel models

Cited by 8 publications

References 21 publications

The COST 2100 MIMO channel model

The COST 2100 MIMO channel model

An Improved DCA and Channel Modelling Algorithm Based on Carrier Priority in LTE/LTE-A

Geometrical Cluster-Based Scatterer Detection Method with the Movement of Mobile Terminal

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