Geometrically Based Channel Model for Indoor Radio Propagation With Directional Antennas

Chen, Yifan; Zhang, Zhenrong; Qin, Tuanfa

doi:10.2528/pierb10022205

Cited by 9 publications

(11 citation statements)

References 29 publications

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“…A semi empirical approach and the analytical model on how to predict the total path loss in various indoor communication links, taking into account the new analytical methods of the derivation of the fading phenomenon between floors and along corridors have been given. In [8], a geometrically based channel model for indoor radio propagation with directional antennas has been given. In [9], a geometry-based statistical model for radio propagation in rectangular office buildings has been presented.…”

Section: Introductionmentioning

confidence: 99%

Propagation Loss Measurement Due to Miscellaneous Phenomenon at 5.6 GHZ Band

Ahmed¹,

Masa‐Campos²,

Campillo³

2012

PIER C

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Abstract-In this work, the propagation loss due to diffraction and insertion losses for indoor scenario at 5.6 GHz band are measured using directive antenna and a Vector Network Analyzer (VNA). It is shown that the insertion loss of a metallic door with porthole window varies from several dB due to the propagation loss via the porthole glass up to 50 dB due to the diffraction by the porthole boards when the line between the transmitting antenna and receiving one is outside the porthole glass. It is shown that the insertion loss of a 12 cm brick wall is 4.8 dB for vertical polarization while it is 6.3 dB for horizontal polarization. Also it is shown the diffraction loss due single or double concrete columns depends on the distance between the transmitting and receiving antennas.

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Section: Introductionmentioning

confidence: 99%

Propagation Loss Measurement Due to Miscellaneous Phenomenon at 5.6 GHZ Band

Ahmed¹,

Masa‐Campos²,

Campillo³

2012

PIER C

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show abstract

“…However, even in this case, considering the simplicity of the model the results are adequate when we can not describe distance statistics in closed-form. At this point, recall that (10), (12) and (15) have been found empirically through simulations but achieve a good trade-off between complexity and accuracy. Obviously, more complex expressions would reduce the modeling error at the cost of higher complexity.…”

Section: Model Validationmentioning

confidence: 99%

“…In our analysis, we develop a geometrical-based method [8][9][10][11][12][13][14][15] and provide simple integral expressions for the cumulative distribution function (cdf) of the distance between nodes that are uniformly located within circular-shaped networks. To the best of the author's knowledge, computation of distance distribution includes awkward expressions and requires time-consuming calculations [5].…”

Section: Introductionmentioning

confidence: 99%

A Geometric Method for Computing the Nodal Distance Distribution in Mobile Networks

Baltzis

2011

PIER

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Abstract-This paper presents a geometrically based method for the calculation of the node-to-node distance distribution function in circular-shaped networks. In our approach, this function is obtained from the intersection volume of a sphere and an ellipsoid. The method is valid for both overlapping and non-overlapping networks. Simulation results and comparisons with methods in the literature demonstrate the efficacy of the approach. The relation between networks geometric parameters and distance statistics is explored. As an application example, we model distance-dependent path loss and investigate the impact of channel characteristics and networks size on signal absorption. The aforementioned model is a useful and lowcomplexity tool for system-level modeling and simulation of mobile communication systems.

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“…Some measurement results also show that the angular pdf in general has a shape which more closely resembles Gaussian or Laplacian pdf [11], while other experiments suggest the use of truncated Gaussian pdf, when the base station is near to the mobile station and truncated Laplacian pdf for micro-cellular radio environments. The effect of antenna directivity on channel characteristics (e.g., angular power distribution) for geometrical-based statistical models have been studied by [18], for macro-cellular and [25,26], for micro-cellular radio environments. For the case when angular distribution of energy around the radio access point and the user equipment, the overall azimuthal response is obtained by multiplying the angle-resolved impulse response with beam pattern.…”

Section: Spatial Correlationmentioning

confidence: 99%

Effect of Steering Error Vector and Angular Power Distributions on Beamforming and Transmit Diversity Systems in Correlated Fading Channel

Umrani¹,

Guan²,

Umrani³

2010

PIER

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Abstract-A comparative analysis of transmit diversity and beamforming for linear and circular antenna arrays in a wireless communications system is presented. The objective is to examine the effect of random perturbations, angular power distributions on transmit diversity and beamforming system. The perturbations are modeled as additive random errors, following complex Gaussian multivariate distribution, to the antenna array steering vectors. Using outage probability, probability of error, and dynamic range of transmitter power as performance measures, we have shown significant effects of array perturbations on the two systems under spatially correlated Rayleigh fading channel. We also examine the effect of angular power distributions (uniform, truncated Gaussian, and truncated Laplacian), which corresponds to different propagation scenario, on the performance of the two systems. Results show that the central angle-of-arrival can Corresponding author: A. W. Umrani (waheed.umrani@faculty.muet.edu.pk). 384Umrani, Guan, and Umrani have significant impact on system performance. And the transmit diversity system with truncated Laplacian distribution performs better as compared to other power distributions, and linear array is a preferable configuration for transmit diversity system. We conclude that array perturbations must not be neglected in the design of transmit diversity and beamforming systems.

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Geometrically Based Channel Model for Indoor Radio Propagation With Directional Antennas

Cited by 9 publications

References 29 publications

Propagation Loss Measurement Due to Miscellaneous Phenomenon at 5.6 GHZ Band

Propagation Loss Measurement Due to Miscellaneous Phenomenon at 5.6 GHZ Band

A Geometric Method for Computing the Nodal Distance Distribution in Mobile Networks

Effect of Steering Error Vector and Angular Power Distributions on Beamforming and Transmit Diversity Systems in Correlated Fading Channel

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