Polarized Channel Model for Body Area Networks Using Reflection Coefficients

Kwon, Seok-Chul; Stuber, G.L.; Lopez, Aida Vera; Papapolymerou, John

doi:10.1109/tvt.2014.2358576

Cited by 11 publications

(3 citation statements)

References 15 publications

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“…In reality, the scatterer is not an ideal conductor and the polarization angle will change according to the reflection coefficients of the scattering material. Our prior work has demonstrated, albeit for different channels, that the reflection coefficients tend to have a secondary effect on channel depolarization [17]. Rather the orientation of the CoP, i.e., the position of certain critical scatterers with respect to the receiver as described by their azimuth and elevation angles, tends to dominate the overall channel depolarization.…”

Section: Geometrical Model Of Wide-band Cellular Down-link Polarimentioning

confidence: 94%

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Wireless Polarized-Channel Simulator

Kwon

Stuber

2014

2014 IEEE 80th Vehicular Technology Conference (VTC2014-Fall)

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A wireless polarized-channel simulator is described that can generate a variety of polarized-channel impulse responses. The simulator is useful in the broad research area of polarization-utilizing wireless communication systems. The simulator relies on a geometrically based statistical model (GBSM) for polarized wide-band channels, and consists of three-dimensional (3-D) concentric scattering cylinders about the mobile station. It can be used to model a polarized wide-band cellular down-link channel. To the best of our knowledge, our polarized-channel simulator is the first such simulation model that can generate the time-variant channel impulse response of polarized wideband wireless fading channels. The simulator utilizes previously reported geometrical theory and reference models for crosspolarization discrimination (XPD), and shows excellent agreement with the reference models, while considering only a finite number of scatterers both for good accuracy and manageable computational complexity.

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Section: Geometrical Model Of Wide-band Cellular Down-link Polarimentioning

confidence: 94%

“…That is, (16), (17), and (19), respectively as follows: Meanwhile, polarization functions described in Section II are the functions of cos θ 6 and cos θ 9 , and we can generate those functions, based on the geometry in Fig. 1 and the law of cosines.…”

Section: Polarized Channel Simulatormentioning

confidence: 99%

Wireless Polarized-Channel Simulator

Kwon

Stuber

2014

2014 IEEE 80th Vehicular Technology Conference (VTC2014-Fall)

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“…The geometrical theory of depolarisation is applied to obtain a geometry-based on-body channel model [ 8 ], where body diffracted, and environment and ground scattered components are taken into account. The same authors also present a modified model [ 9 ], which considers the depolarisation due to different Fresnel’s reflection coefficients; one should note that this model considers only static users, since fixed orientations of the Tx and Rx antennas are assumed. The influence of body dynamics is considered in [ 10 ], by using animation software to extract motion patterns and apply them to a body phantom in electromagnetic simulations software; as simulations were performed for free space, the authors consider only depolarisation originating from electromagnetic wave interaction with the body, and Tx-Rx antennas’ mismatch due to antenna rotation and tilting during motion.…”

Section: Introductionmentioning

confidence: 99%

Characteristics of the polarised off-body channel in indoor environments

Turbic

Ambroziak

Correia

2017

J Wireless Com Network

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This paper addresses the depolarisation effect in off-body body area networks channels, based on measurements performed at 2.45 GHz in an indoor environment. Seven different scenarios, involving both static and dynamic users, were considered, taking a statistical perspective. The analysis of the cross-polarisation discrimination is performed, as well as the analysis of path loss in co- and cross-polarised channels. Results show a strong dependence of the cross-polarisation discrimination and of channel characteristics on the polarisation and propagation condition, i.e. line-of-sight (LoS), non-LoS or quasi-LoS. Distance, varied between 1 and 6 m in the considered scenarios, is observed to have very little impact on the cross-polarisation discrimination. In the considered dynamic scenario, the channel is characterised by lognormal-distributed shadowing and Nakagami-distributed multipath fading. Parameters of the Nakagami distribution have essentially different values in the co- and cross-polarised channels, showing a trend towards Rice in the former and Rayleigh in the latter. Based on results, a model is proposed for a dynamic off-body channel.

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User Influence on Polarization Characteristics in Off-Body Channels

et al. 2020

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This paper investigates the impact of the user's body on wearable antenna radiation characteristics and the consequent effects on the off-body channel, with the focus on the polarization aspect. The impact on antenna gain and polarization is analyzed for different antenna placements and separations from the body, based on electromagnetic simulations with numerical phantoms at 3, 4 and 5 GHz. Results show a strong influence of the body on the antenna efficiency, gain, and polarization. The excess losses due to body-shadowing suppress the antenna radiation behind the body by more than 20 dB, while its polarization changes from vertical in free space, to an elliptical one when placed on the body. The obtained radiation characteristics are then employed for off-body channel simulations using a geometrybased polarized channel model, which employs an analytic mobility model for wearable antennas based on Fourier series. The antenna rotation due to changes in user's posture is seen as one of the main sources of offbody channel degradation. The polarization mismatch losses imposed by antennas' physical misalignment, are observed to yield periodic fades of the Line-of-Sight component, with more than 30 dB drops in the received power level.

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Polarized Channel Model for Body Area Networks Using Reflection Coefficients

Cited by 11 publications

References 15 publications

Wireless Polarized-Channel Simulator

Wireless Polarized-Channel Simulator

Characteristics of the polarised off-body channel in indoor environments

User Influence on Polarization Characteristics in Off-Body Channels

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