The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
IEEE 802.11ad-Based Radar: An Approach to Joint Vehicular Communication-Radar System
Open accessAbstract
Millimeter-wave (mmWave) radar is widely used in vehicles for applications such as adaptive cruise control and collision avoidance. In this paper, we propose an IEEE 802.11ad-based radar for long-range radar (LRR) applications at the 60 GHz unlicensed band. We exploit the preamble of a single-carrier physical layer frame, which consists of Golay complementary sequences with good correlation properties that make it suitable for radar. This system enables a joint waveform for automotive radar and a potential mmWave vehicular communication system based on the mmWave consumer wireless local area network standard, allowing hardware reuse. To formulate an integrated framework of vehicle-to-vehicle communication and LRR, we make typical assumptions for LRR applications, incorporating the full duplex radar operation. This new feature is motivated by the recent development of systems with sufficient isolation and self-interference cancellation. We develop single- and multi-frame radar receiver algorithms for target detection as well as range and velocity estimation for both single- and multi-target scenarios. Our proposed radar processing algorithms leverage channel estimation and time-frequency synchronization techniques used in a conventional IEEE 802.11ad receiver with minimal modifications. Analysis and simulations show that in a single-target scenario, a gigabits-per-second data rate is achieved simultaneously with cm-level range accuracy and cm/s-level velocity accuracy. The target vehicle is detected with a high probability (above 99.99$\%$) at a low false alarm rate of 10$^{-6}$ for an equivalent isotropically radiated power of 40 dBm up to a vehicle separation distance of about 200 m. The proposed IEEE 802.11ad-based radar meets the minimum accuracy/resolution requirement of range and velocity estimates for LRR applications.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
(2012) · doi:10.1109/ieeestd.2012.6392842 · Cited by 191
Cited by
Integrated Sensing and Communications: Toward Dual-Functional Wireless Networks for 6G and Beyond
Liu, F., Cui, Y., Masouros, C., Xu, J., Han, T. X., Eldar, Y. C., & Buzzi, S. (2022) · IEEE Journal on Selected Areas in Communications · doi:10.1109/jsac.2022.3156632 · Cited by 3,857
Joint Transmit Beamforming for Multiuser MIMO Communications and MIMO Radar
Liu, X., Huang, T., Shlezinger, N., Liu, Y., Zhou, J., & Eldar, Y. C. (2020) · IEEE Transactions on Signal Processing · doi:10.1109/tsp.2020.3004739 · Cited by 992
Noor-A-Rahim, M., Liu, Z., Lee, H., Khyam, M. O., He, J., Pesch, D., Moessner, K., Saad, W., & Poor, H. V. (2022) · Proceedings of the IEEE · doi:10.1109/jproc.2022.3173031 · Cited by 737
Integrated Sensing and Communication Signals Toward 5G-A and 6G: A Survey
Wei, Z., Qu, H., Wang, Y., Yuan, X., Wu, H., Du, Y., Han, K., Zhang, N., & Feng, Z. (2023) · IEEE Internet of Things Journal · doi:10.1109/jiot.2023.3235618 · Cited by 686
Secure Transmission Scheme Based on Joint Radar and Communication in Mobile Vehicular Networks
Yao, Y., Shu, F., Li, Z., Cheng, X., & Wu, L. (2023) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2023.3271452 · Cited by 278
Metadata
- Authors
- Kumari, P., Choi, J., Gonzalez-Prelcic, N., & Heath, R. W.
- Venue
- IEEE Transactions on Vehicular Technology
- Published
- 2018-04
- Volume
- 67
- Issue
- 4
- Pages
- 3012-3027
- ISSN
- 0018-9545 (ISSN-L)
- 1939-9359
- OpenAlex
- W2590141315
- Cited by
- 704
- References
- 1
- FWCI
- 37.24
- Type
- journal article
- Language
- en
- Open access
- green
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: IEEE 802.11ad-Based Radar: An Approach to Joint Vehicular Communication-Radar System. https://app.cochat.ai/papers/10.1109/tvt.2017.2774762
- The paper
- Kumari, P., Choi, J., Gonzalez-Prelcic, N., & Heath, R. W. (2018). IEEE 802.11ad-Based Radar: An Approach to Joint Vehicular Communication-Radar System. IEEE Transactions on Vehicular Technology. https://doi.org/10.1109/tvt.2017.2774762
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.