Millimeter-Wave Human Blockage at 73 GHz with a Simple Double Knife-Edge Diffraction Model and Extension for Directional Antennas

MacCartney, George R.; Deng, Sijia; Sun, Shu; Rappaport, Theodore S.

doi:10.1109/vtcfall.2016.7881087

Cited by 158 publications

(162 citation statements)

References 17 publications

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“…However, Collonge et al reported in [148] that the severity of human shadowing is not influenced directly by the number of blocking persons, but rather by the Tx and Rx antenna configurations, such as patch and horn antennas [148]. This was in fact substantiated by MacCartney et al in their double diffraction human blockage model proposed in [150], where their results showed that in addition to the human blockage effect, the severe shadowing is conjointly subsidized with the antenna brand employed. Furthermore, MacCartney et al stressed that using electronically steerable and highgain directional antennas, the human shadowing is reduced.…”

Section: G Other Propagation Factorsmentioning

confidence: 97%

Millimeter-Wave Communications: Physical Channel Models, Design Considerations, Antenna Constructions, and Link-Budget

Hemadeh

Satyanarayana

El‐Hajjar

et al. 2018

IEEE Commun. Surv. Tutorials

554

393

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Abstract-The millimeter wave (mmWave) frequency band spanning from 30 GHz to 300 GHz constitutes a substantial portion of the unused frequency spectrum, which is an important resource for future wireless communication systems in order to fulfill the escalating capacity demand. Given the improvements in integrated components and enhanced power efficiency at high frequencies, wireless systems can operate in the mmWave frequency band. In this paper, we present a survey of the mmWave propagation characteristics, channel modeling and design guidelines, such as system and antenna design considerations for mmWave, including the link budget of the network, which are essential for mmWave communication systems. We commence by introducing the main channel propagation characteristics of mmWaves followed by channel modeling and design guidelines. Then, we report on the main measurement and modeling campaigns conducted in order to understand the mmWave band's properties and present the associated channel models. We survey the different channel models focusing on the channel models available for the 28 GHz, 38 GHz, 60 GHz and 73 GHz frequency bands. Finally, we present the mmWave channel model and its challenges in the context of mmWave communication systems design.

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Section: G Other Propagation Factorsmentioning

confidence: 97%

Millimeter-Wave Communications: Physical Channel Models, Design Considerations, Antenna Constructions, and Link-Budget

Hemadeh

Satyanarayana

El‐Hajjar

et al. 2018

IEEE Commun. Surv. Tutorials

554

393

View full text Add to dashboard Cite

show abstract

“…However, as mentioned in Section I, a human blockage occurs aperiodically in mmWave communications and there are no signs of the blockage several hundred milliseconds before the 6 blockage occurs. Therefore, although it is possible to reactively estimate the signal attenuation induced by the human blockage, it is difficult to predict the human blockage before it occurs Another approach to predict the received power is a ray-tracing simulation [28]- [30]. If a perfect geometry of a future communication environment, i.e., future positions, shapes, and materials of all the things in the environment (e.g., pedestrians, furniture, and walls), can be obtained, the ray-tracing simulation can calculate all the possible signal propagation and predict the received power.…”

Section: Related Workmentioning

confidence: 99%

Proactive Received Power Prediction Using Machine Learning and Depth Images for mmWave Networks

Nishio¹,

Okamoto²,

Nakashima³

et al. 2019

IEEE J. Select. Areas Commun.

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This study demonstrates the feasibility of the proactive received power prediction by leveraging spatiotemporal visual sensing information toward the reliable millimeter-wave (mmWave) networks.Since the received power on a mmWave link can attenuate aperiodically due to a human blockage, the long-term series of the future received power cannot be predicted by analyzing the received signals before the blockage occurs. We propose a novel mechanism that predicts a time series of the received power from the next moment to even several hundred milliseconds ahead. The key idea is to leverage the camera imagery and machine learning (ML). The time-sequential images can involve the spatial geometry and the mobility of obstacles representing the mmWave signal propagation. ML is used to build the prediction model from the dataset of sequential images labeled with the received power in several hundred milliseconds ahead of when each image is obtained. The simulation and experimental evaluations using IEEE 802.11ad devices and a depth camera show that the proposed mechanism employing convolutional LSTM predicted a time series of the received power in up to 500 ms ahead at an inference time of less than 3 ms with a root-mean-square error of 3.5 dB.Parts of this work were presented at the 85th IEEE Vehicular Technology Conference (VTC Spring) and the IEEE Consumer Communications and Networking Conference (CCNC). 2 Index Terms millimeter-wave communications, link quality prediction, proactive prediction, machine learning, supervised learning, depth image Received power (dBm) Grand truth (a) When the camera was at A low . Received power (dBm) Grand truth (b) When the camera was at A high .

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“…In the mmWave VR system, the signal may be interrupted by a user experiencing the VR content or other obstacles in the room. As the VR device and content server in the mmWave link must employ a directional antenna to concentrate power and compensate for the high path loss, this problem becomes more severe . The user experiencing the content may interfere with the establishment of a clear LOS between the device and the content server because of various obstacles such as the user's hand, head, and action, resulting in the attenuation of the received SNR (see Figure B).…”

Section: Research Challenges For Mmwave Vrmentioning

confidence: 99%

Simulation and measurement: Feasibility study of Tactile Internet applications for mmWave virtual reality

Dao

Kim

et al. 2020

ETRI Journal

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Numerous wearable technology companies have recently developed several head‐mounted display (HMD) products for virtual reality (VR) services. 5G wireless networks aim at providing high‐quality 3D multimedia services such as VR, augmented reality, and mixed reality. In this study, we examine the application of millimeter‐wave (mmWave) technology to realize low‐latency wireless communication between an HMD and its content server. However, the propagation characteristics of mmWave present several challenges such as the deafness, blockage, and beam alignment problems, and interference among content servers. In this study, we focus on an environment that provides VR services in the mmWave band and introduce existing techniques for addressing such challenges. In addition, we employ a commercialized IEEE 802.11ad VR dongle to measure the actual data rate of an mmWave VR application and identify the degree to which the performance deteriorates when the above problems occur. Finally, we verify the feasibility of the proposed solutions through a simulation of several VR scenarios in the mmWave band.

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Millimeter-Wave Human Blockage at 73 GHz with a Simple Double Knife-Edge Diffraction Model and Extension for Directional Antennas

Cited by 158 publications

References 17 publications

Millimeter-Wave Communications: Physical Channel Models, Design Considerations, Antenna Constructions, and Link-Budget

Millimeter-Wave Communications: Physical Channel Models, Design Considerations, Antenna Constructions, and Link-Budget

Proactive Received Power Prediction Using Machine Learning and Depth Images for mmWave Networks

Simulation and measurement: Feasibility study of Tactile Internet applications for mmWave virtual reality

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