2014 XXXIth URSI General Assembly and Scientific Symposium (URSI GASS) 2014
DOI: 10.1109/ursigass.2014.6929648
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Directional characterization of the 60 GHz indoor-office channel

Abstract: Directional, dual-link, quad-polarized 60 GHz channel measurements have been carried out in a small-office environment. Purpose of the measurements is to study the directional properties of the channel in view of future multi-gigabit system adopting beam-forming or macro-diversity solutions. The impact of polarization on the characteristics of the channel is also addressed in the study.

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Cited by 37 publications
(29 citation statements)
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“…The works [60], [94] on the other hand report a larger number of directions available in similar dense urban environments, with no information of the angular spread. The indoor channel sounding [70] shows clear clustering of multipaths according to the PAS and power angular-delay profiles. In contrast, there are also works reporting PAS spread over wide angular range; [71] shows PAS of outdoor rooftop-to-ground channels at 28 GHz, revealing rich scattering even in LOS cases.…”
Section: Power Delay Profilesmentioning
confidence: 98%
See 1 more Smart Citation
“…The works [60], [94] on the other hand report a larger number of directions available in similar dense urban environments, with no information of the angular spread. The indoor channel sounding [70] shows clear clustering of multipaths according to the PAS and power angular-delay profiles. In contrast, there are also works reporting PAS spread over wide angular range; [71] shows PAS of outdoor rooftop-to-ground channels at 28 GHz, revealing rich scattering even in LOS cases.…”
Section: Power Delay Profilesmentioning
confidence: 98%
“…The maximum angular spread is observed in a uniform power spectrum that yields azimuth and elevation angular spread in degree of 104 • and 52 • . [70] reports angular spreads of an indoor NLOS channel for different Tx and Rx antenna polarizations, showing that they vary about ±40% and ±10% around the median value on the azimuth and elevation domains, respectively. The angular spread values in outdoor cellular scenarios are presently lacking, though there have been several measurements that allow for them, e.g., [24], [28], [71].…”
Section: Large-scale Modelsmentioning
confidence: 99%
“…This results in a lower specular reflectivity of the surface in favour of diffuse reflection where each impinging ray is back-scattered into many low-amplitude rays having random propagation directions. Although some authors hypothesized for this reason a stronger Dense Multipath Component (DMC [32]) at mm-wave frequencies compared to lower frequencies, recent studies have shown that the actual ratio of the DMC to the Specular Component is similar [33][27], or even lower [34]. Probably the higher degree of rough-surface scattering for some surfaces is overcompensated by the lower level of multipath-richness due to the suppression of through-wall propagation and by lower diffraction effects.…”
Section: Propagation Characteristicsmentioning
confidence: 99%
“…Due to the very small wavelength highly accurate positioners on the order of a fraction of a wavelength to synthesize the array, and sources with low phase noise and high stability would be needed to apply high resolution estimation algorithms. Multiple antenna measurements enable the estimation of the specular multipath component (SMC) parameters including the AoD and AoA using high resolution algorithms such as SAGE [43] or RIMAX [33] [44]. A drawback of SAGE is that 1) the computational load is dependent on the covariance matrix size which can be excessively huge for typical MIMO measurements and 2) it only assumes additive white Gaussian noise in the model and thus does not include dense multipath components (DMC).…”
Section: Mm-wave Channel Soundingmentioning
confidence: 99%
“…This is usually achieved through measurement campaigns [9,10] or exploiting ray tracing (RT) prediction models [11][12][13][14], which can in principle simulate the multipath channel. It is worth noticing that the computation capabilities provided by today's multicore processors and graphical processing units (GP-GPUs) can cope with the computational burden required by RT simulations, thus partly removing the bottleneck that used to limit the massive use of RT models [15].…”
mentioning
confidence: 99%