The DOI matches its Crossref record; 14 of the 16 references it cites were found in a registry or an index.
Propagation Channels for mmWave Vehicular Communications: State-of-the-art and Future Research Directions
Open accessAbstract
Vehicular communications essentially support automotive applications for safety and infotainment. For this reason, industry leaders envision an enhanced role for vehicular communications in the fifth generation of mobile communications technology. Over the years, the number of vehicle- mounted sensors has increased steadily, which potentially leads to more volume of critical data communications in a short time. Also, emerging applications such as remote/autonomous driving and infotainment such as high-definition movie streaming require data-rates on the order of multiple Gb/s. Such high data rates require a large system bandwidth, but very limited bandwidth is available in the sub-6 GHz cellular bands. This has sparked research interest in the millimeter wave (mmWave) band (10 GHz-300 GHz), where a large bandwidth is available to support the high data rate and low latency communications envisioned for emerging vehicular applications. However, leveraging mmWave communications requires a thorough understanding of the relevant vehicular propagation channels, which are significantly different from those investigated below 6 GHz. Despite their significance, very few investigations of mmWave vehicular channels are reported in the literature. This work highlights the key attributes of mmWave vehicular communication channels and surveys the recent literature on channel characterization efforts in order to provide a gap analysis and propose possible directions for future research.
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“Massive Multiple-Input Multiple-Output (M-MIMO) systems and millimeter-Wave (mmWave) spectrum exploiting high spatial resolution and multi-gigahertz bandwidth, respectively, are believed to have an important role in addressing the capacity demands of future communication networks [12,22].”
From Quantum Machine Learning for 6G Communication Networks: State-of-the-Art and Vision for the Future (2019) · cites this paper as [22]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
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“Moreover, in vehicular communication context, the carrier frequency being a linear scaling factor causes very high Doppler shift/spread even in very low mobility conditions (e.g., even vehicle engine vibrations can cause high Doppler shift [22]).”
From Quantum Machine Learning for 6G Communication Networks: State-of-the-Art and Vision for the Future (2019) · cites this paper as [22]
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Cites
5G: A Tutorial Overview of Standards, Trials, Challenges, Deployment, and Practice
Shafi, M., Molisch, A. F., Smith, P. J., Haustein, T., Zhu, P., Silva, P. D., Tufvesson, F., Benjebbour, A., & Wunder, G. (2017) · IEEE Journal on Selected Areas in Communications · doi:10.1109/jsac.2017.2692307 · Cited by 2,312
Rappaport, T. S., MacCartney, G. R., Samimi, M. K., & Sun, S. D. (2015) · IEEE Transactions on Communications · doi:10.1109/tcomm.2015.2434384 · Cited by 1,591
On mm-Wave Multipath Clustering and Channel Modeling
Gustafson, C., Haneda, K., Wyne, S., & Tufvesson, F. (2014) · IEEE Transactions on Antennas and Propagation · doi:10.1109/tap.2013.2295836 · Cited by 298
Self-citationThe Impact of Beamwidth on Temporal Channel Variation in Vehicular Channels and Its Implications
Va, V., Choi, J. J., & Heath, R. W. (2016) · IEEE Transactions on Vehicular Technology · doi:10.1109/tvt.2016.2622164 · Cited by 259
Geometrical-Based Modeling for Millimeter-Wave MIMO Mobile-to-Mobile Channels
He, R., Ai, B., Stüber, G. L., Wang, G., & Zhong, Z. D. (2017) · IEEE Transactions on Vehicular Technology · doi:10.1109/tvt.2017.2774808 · Cited by 224
Inverse Multipath Fingerprinting for Millimeter Wave V2I Beam Alignment
Va, V., Choi, J. J., Shimizu, T., Bansal, G., & Heath, R. W. (2017) · IEEE Transactions on Vehicular Technology · doi:10.1109/tvt.2017.2787627 · Cited by 220
Millimeter-Wave Communication with Out-of-Band Information
Gonzalez-Prelcic, N., Ali, A., Va, V., & Heath, R. W. (2017) · IEEE Communications Magazine · doi:10.1109/mcom.2017.1700207 · Cited by 137
Modeling and Design of Millimeter-Wave Networks for Highway Vehicular Communication
Tassi, A., Egan, M., Piechocki, R. J., & Nix, A. (2017) · IEEE Transactions on Vehicular Technology · doi:10.1109/tvt.2017.2734684 · Cited by 136
MmWave Vehicle-to-Infrastructure Communication: Analysis of Urban Microcellular Networks
Wang, Y., Venugopal, K., Molisch, A. F., & Heath, R. W. (2018) · IEEE Transactions on Vehicular Technology · doi:10.1109/tvt.2018.2827259 · Cited by 108
Петров, В. И., Kokkoniemi, J., Moltchanov, D., Lehtomäki, J. J., Juntti, M. J., & Koucheryavy, Y. A. (2018) · IEEE Transactions on Vehicular Technology · doi:10.1109/tvt.2018.2799564 · Cited by 76
Karttunen, A., Molisch, A. F., Hur, S., Park, J.-H., & Zhang, J. C. (2017) · IEEE Transactions on Wireless Communications · doi:10.1109/twc.2017.2749570 · Cited by 74
Blumenstein, J., Prokeš, A., Chandra, A., Mikulášek, T., Maršálek, R., Zemen, T., & Mecklenbräuker, C. F. (2016) · IEEE Transactions on Vehicular Technology · doi:10.1109/tvt.2016.2600101 · Cited by 50
Millimeter-Wave V2X Channels: Propagation Statistics, Beamforming, and Blockage
Anjinappa, C. K., & Güvenç, İ. (2018) · IEEE Vehicular Technology Conference · doi:10.1109/vtcfall.2018.8690733 · Cited by 28
Effects of vehicle vibrations on mm-wave channel: Doppler spread and correlative channel sounding
Blumenstein, J., Vychodil, J., Pospíšil, M., Mikulášek, T., & Prokeš, A. (2016) · IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC) · doi:10.1109/pimrc.2016.7794619 · Cited by 20
Research works printed but not linked: 1
- 10.1109/TWC.2017.2703109 · DOI
Cited by
Sorted by citations
Quantum Machine Learning for 6G Communication Networks: State-of-the-Art and Vision for the Future
Nawaz, S. J., Sharma, S. K., Wyne, S., Patwary, M. N., & Asaduzzaman, M. (2019) · IEEE Access · doi:10.1109/access.2019.2909490 · Cited by 658
Self-citationA Survey on 5G Millimeter Wave Communications for UAV-Assisted Wireless Networks
Zhang, L., Zhao, H. M., Hou, S., Zhao, Z. W., Xu, H., Wu, X., Wu, Q., & Zhang, R. (2019) · IEEE Access · doi:10.1109/access.2019.2929241 · Cited by 359
Beamforming Technologies for Ultra-Massive MIMO in Terahertz Communications
Ning, B., Tian, Z., Mei, W., Chen, Z., Han, C. Z., Li, S., Yuan, J., & Zhang, R. (2023) · IEEE Open Journal of the Communications Society · doi:10.1109/ojcoms.2023.3245669 · Cited by 286
Cognition in UAV-Aided 5G and Beyond Communications: A Survey
Ullah, Z., Al-Turjman, F., & Mostarda, L. (2020) · IEEE Transactions on Cognitive Communications and Networking · doi:10.1109/tccn.2020.2968311 · Cited by 226
Chaloun, T., Boccia, L., Arnieri, E., Fischer, M. D., Valenta, V., Fonseca, N. J. G., & Waldschmidt, C. (2022) · IEEE Journal of Microwaves · doi:10.1109/jmw.2022.3202626 · Cited by 133
Metadata
- Authors
- Jameel, F., Wyne, S., Nawaz, S. J., & Chang, Z.
- Affiliations
- University of Jyväskylä (FI)
- COMSATS University Islamabad (PK)
- Venue
- IEEE Wireless Communications
- Published
- 2019-02
- Volume
- 26
- Issue
- 1
- Pages
- 144-150
- ISSN
- 1536-1284 (ISSN-L)
- 1558-0687
- OpenAlex
- W2902466218
- Cited by
- 107
- References
- 16
- Citations by year
- 2026: 5 · 2025: 8 · 2024: 9 · 2023: 14 · 2022: 19 · 2021: 15 · 2020: 24 · 2019: 13
- FWCI
- 4.96
- Type
- journal article
- Language
- en
- Open access
- green
- urn.fi
- Licence
- Locations
- IEEE Wireless Communications (publishedVersion)
- Jyväskylä University Digital Archive (University of Jyväskylä) (submittedVersion)
- Topics
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Millimeter-Wave Propagation and Modeling
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Vehicular Ad Hoc Networks (VANETs)
- Physical Sciences › Engineering › Aerospace Engineering › Radar Systems and Signal Processing
- Keywords
- millimeter-wave communication, vehicular communication, propagation channel, channel characterization, channel modeling, 5G, autonomous driving, infotainment, high-speed data transmission, bandwidth
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