The DOI matches its Crossref record; 11 of the 11 references it cites were found in a registry or an index.
Performance Analysis of Joint Radar and Communication using OFDM and OTFS
Open accessAbstract
We consider a joint radar estimation and communication system using orthogonal frequency division multiplexing (OFDM) and orthogonal time frequency space (OTFS) modulations. The scenario is motivated by vehicular applications where a vehicle equipped with a mono-static radar wishes to communicate data to its target receiver, while estimating parameters of interest related to this receiver. By focusing on the case of a single target, we derive the maximum likelihood (ML) estimator and the Cramer-Rao lower bound on joint velocity and range estimation. Numerical examples demonstrate that both digital modulation formats can achieve as accurate range/velocity estimation as state-of-the-art radar waveforms such as frequency modulated continuous wave (FMCW) while sending digital information at their full achievable rate. We conclude that it is possible to obtain significant data transmission rate without compromising the radar estimation capabilities of the system.
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“According to [43,44], the radar sensing performance of NR-V2X signals with OFDM waveforms is represented by the Cramér–Rao Lower Bound (CRLB) on distance estimation variances.”
From Reinforcement Learning-Based Resource Allocation Scheme of NR-V2X Sidelink for Joint Communication and Sensing (2025) · cites this paper as [43]
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Citations
Cites
MIMO Radar with Colocated Antennas
Li, J., & Stoica, P. (2007) · IEEE Signal Processing Magazine · doi:10.1109/msp.2007.904812 · Cited by 2,591
Sturm, C., & Wiesbeck, W. (2011) · Proceedings of the IEEE · doi:10.1109/jproc.2011.2131110 · Cited by 1,461
Interference Cancellation and Iterative Detection for Orthogonal Time Frequency Space Modulation
Raviteja, P., Phan, K. T., Hong, Y., et al. (2018) · IEEE Transactions on Wireless Communications · doi:10.1109/twc.2018.2860011 · Cited by 1,262
Automotive radars: A review of signal processing techniques
Patole, S., Torlak, M., Wang, D., & Ali, M. (2017) · IEEE Signal Processing Magazine · doi:10.1109/msp.2016.2628914 · Cited by 1,208
IEEE 802.11ad-Based Radar: An Approach to Joint Vehicular Communication-Radar System
Kumari, P., Choi, J. J., Prelcic, N. G., & Heath, R. W. (2017) · IEEE Transactions on Vehicular Technology · doi:10.1109/tvt.2017.2774762 · Cited by 707
OFDM Radar Algorithms in Mobile Communication Networks
Braun, K. M. (2014) · Repository KITopen (Karlsruhe Institute of Technology) · doi:10.5445/ir/1000038892 · Cited by 166
Joint State Sensing and Communication: Optimal Tradeoff for a Memoryless Case
Kobayashi, M., Caire, G., & Kramer, G. G. (2018) · IEEE International Symposium on Information Theory (ISIT) · doi:10.1109/isit.2018.8437621 · Cited by 151
Self-citationTime-Frequency Foundations of Communications: Concepts and Tools
Matz, G., Bölcskei, H., & Hlawatsch, F. (2013) · IEEE Signal Processing Magazine · doi:10.1109/msp.2013.2269702 · Cited by 112
Cordeiro, C. D. M., Akhmetov, D., & Park, M. (2010) · doi:10.1145/1859964.1859968 · Cited by 86
Delay and Doppler processing for multi-target detection with IEEE 802.11 OFDM signaling
Nguyen, D. H. N., & Heath, R. W. (2017) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp.2017.7952790 · Cited by 54
Orthogonal Time Frequency Space (OTFS) Modulation Based Radar SystemPreprint
Raviteja, P., Phan, K. T., Hong, Y., et al. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1901.09300 · Cited by 6
Research works printed but not linked: 1
- richards, 2014, Fundamentals of Radar Signal Processing
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Sorted by citations
Limited feedforward waveform design for OFDM dual-functional radar-communications
Keskin, M. F., Koivunen, V., & Wymeersch, H. (2021) · IEEE Transactions on Signal Processing · doi:10.1109/tsp.2021.3076894 · Cited by 188
Sidelink 5G-V2X for Integrated Sensing and Communication: the Impact of Resource Allocation
Bartoletti, S., Decarli, N., & Masini, B. M. (2022) · 2022 IEEE International Conference on Communications Workshops (ICC Workshops) · doi:10.1109/iccworkshops53468.2022.9814586 · Cited by 26
Li, Z., Wang, P., Shen, Y., & Li, S. (2025) · Sensors · doi:10.3390/s25020302 · Cited by 15
Metadata
- Authors
- Gaudio, L., Kobayashi, M., Bissinger, B., & Caire, G.
- Affiliations
- University of Parma (IT)
- Technical University of Munich (DE)
- Technische Universität Berlin (DE)
- Venue
- 2019 IEEE International Conference on Communications Workshops (ICC Workshops)
- Publisher
- IEEE
- Published
- 2019-05
- Pages
- 1-6
- ISSN
- 2164-7038 (ISSN-L)
- OpenAlex
- W2913265698
- Semantic Scholar
- 3580af51f32078cfb5fd739d03642e063d38e104
- Cited by
- 132
- References
- 11
- Citations by year
- 2026: 6 · 2025: 30 · 2024: 28 · 2023: 30 · 2022: 15 · 2021: 14 · 2020: 3 · 2019: 6
- FWCI
- 17.25
- Type
- conference paper
- Language
- en
- Open access
- green
- arxiv.org
- Licence
- Locations
- IEEE International Conference on Communications workshops (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- arXiv (Cornell University)
- Funders
- Fondazione Cariparma
- Topics
- Physical Sciences › Engineering › Aerospace Engineering › Radar Systems and Signal Processing
- Physical Sciences › Engineering › Aerospace Engineering › Advanced SAR Imaging Techniques
- Physical Sciences › Engineering › Electrical and Electronic Engineering › PAPR reduction in OFDM
- Keywords
- joint radar-communication, OFDM, orthogonal time frequency space, Cramer-Rao lower bound, maximum likelihood estimation, range estimation, velocity estimation, automotive radar, digital modulation
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