Modelling of the land mobile satellite channel using a virtual city approach

Fontán, F.P.; Abele, A.; Montenegro, B.; Lacoste, F.; Fabbro, Vincent; Castanet, Laurent; Sanmartín, B.; Valtr, Pável

doi:10.1049/ic.2007.1245

Cited by 5 publications

(3 citation statements)

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“…In the Kirchhoff KED model [37], [38], the Kirchhoff diffraction equation is used to simulate loss caused by human blockages. Assume S is a screen extended infinitely in the X-Y plane, S 0 refers to the aperture on the screen, Q 0 (x 0 , y 0 , z 0 ) is the intersection point of the Tx-Rx connecting line with the aperture, d 1 and d 2 denote the projection of Tx-Q 0 and Rx-Q 0 on Z axis, respectively.…”

Section: B Blockage Modelmentioning

confidence: 99%

Multi-Frequency Multi-Scenario Millimeter Wave MIMO Channel Measurements and Modeling for B5G Wireless Communication Systems

Huang

Wang

Chang

et al. 2020

IEEE J. Select. Areas Commun.

112

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Millimeter wave (mmWave) bands have been utilized for the fifth generation (5G) communication systems and will no doubt continue to be deployed for beyond 5G (B5G). However, the underlying channels are not fully investigated at multifrequency bands and in multi-scenarios by using the same channel sounder, especially for the outdoor, multiple-input multipleoutput (MIMO), and vehicle-to-vehicle (V2V) conditions. In this paper, we conduct multi-frequency multi-scenario mmWave MIMO channel measurements with 4×4 antennas at 28, 32, and 39 GHz bands for three cases, i.e., the human body and vehicle blockage measurements, outdoor path loss measurements, and V2V measurements. The channel characteristics, including blockage effect, path loss and coverage range, and non-stationarity and spatial consistency, are thoroughly studied. The blockage model, path loss model, and time-varying channel model are proposed for mmWave MIMO channels. The channel measurement and modeling results will be of great importance for further mmWave communication system deployments in indoor hotspot, outdoor, and vehicular network scenarios for B5G. Index Terms-Millimeter wave bands, MIMO vehicle-tovehicle, B5G wireless communication systems, multi-frequency channel measurements, channel modeling.

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Section: B Blockage Modelmentioning

confidence: 99%

Multi-Frequency Multi-Scenario Millimeter Wave MIMO Channel Measurements and Modeling for B5G Wireless Communication Systems

Huang

Wang

Chang

et al. 2020

IEEE J. Select. Areas Commun.

112

View full text Add to dashboard Cite

show abstract

“…During walking, the positions of the Tx and Rx antennas vary in accordance to the angular variations of the corresponding body parts shown in Figure 4 (for v r = 1). The time-varying diffracted signal can then be calculated using Kirchhoff diffraction equation [21,22] which gives the relationship between the aperture diffracted electric field at an observation point, P, and the free-space electric field…”

Section: Shadowingmentioning

confidence: 99%

Time-varying on-body wireless channel model during walking

Cheffena

2014

J Wireless Com Network

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A novel dynamic channel model for on-body wireless communication during walking is proposed. The developed model utilizes a human walking model which provides detailed information on the movement of the human body parts. The diffraction of the signal around the body parts is used to describe the time-varying shadowing effects. Body part movements are also used to estimate the signal fading caused by angular variations of the transmitting and receiving antenna gains. A Rice distribution is used to represent the multipath fading effects caused by objects around the human body. Simulation results of the first-and second-order statistics of the received signal affected by moving body parts for 2.4 GHz signal are presented. To illustrate the capabilities of the developed model, time series were generated and used in system performance calculations. The obtained results give an insight into the potential advantages of link diversity technique in wireless body area networks (WBANs).

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“…The diffracted signal can be calculated using Kirchhoff diffraction equation [10,11] which gives the relationship between the aperture diffracted electric field at an observation point, P, and the freespace electric field…”

Section: Diffractionmentioning

confidence: 99%

Physical-statistical channel model for signal effect by moving human bodies

Cheffena

2012

J Wireless Com Network

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A novel physical-statistical channel model for simulating the signal effect by moving human bodies is presented. The human body is modeled as vertically oriented dielectric cylindrical volume. The received signal is assumed to be composed of a direct component which might be subject to shadowing and a multipath component due to reflection and diffuse scattering, i.e., a Ricean channel. The shadowing effect of the direct signal component is calculated using Kirchhoff diffraction equation. The multipath component is parameterized by calculating the reflected fields from the floor, ceiling and walls of the indoor environment as well as scattered fields from moving human bodies. Poisson and Exponential distributions are used to describe the shadowing and inter-shadowing events caused by multiple bodies, respectively. Furthermore, simulation results of the first and second order statistics of the received signal affected by moving human bodies for 3.35 GHz and 60 GHz signals are presented. In addition, initial validation of the developed model are performed using an empirical model for human body shadowing and reported measurement results.

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Modelling of the land mobile satellite channel using a virtual city approach

Cited by 5 publications

References 0 publications

Multi-Frequency Multi-Scenario Millimeter Wave MIMO Channel Measurements and Modeling for B5G Wireless Communication Systems

Multi-Frequency Multi-Scenario Millimeter Wave MIMO Channel Measurements and Modeling for B5G Wireless Communication Systems

Time-varying on-body wireless channel model during walking

Physical-statistical channel model for signal effect by moving human bodies

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