Toward Millimeter Wave Joint Radar-Communications: A Signal Processing Perspective
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Abstract (arXiv)
Synergistic design of communications and radar systems with common spectral and hardware resources is heralding a new era of efficiently utilizing a limited radio-frequency spectrum. Such a joint radar-communications (JRC) model has advantages of low-cost, compact size, less power consumption, spectrum sharing, improved performance, and safety due to enhanced information sharing. Today, millimeter-wave (mm-wave) communications have emerged as the preferred technology for short distance wireless links because they provide transmission bandwidth that is several gigahertz wide. This band is also promising for short-range radar applications, which benefit from the high-range resolution arising from large transmit signal bandwidths. Signal processing techniques are critical in implementation of mmWave JRC systems. Major challenges are joint waveform design and performance criteria that would optimally trade-off between communications and radar functionalities. Novel multiple-input-multiple-output (MIMO) signal processing techniques are required because mmWave JRC systems employ large antenna arrays. There are opportunities to exploit recent advances in cognition, compressed sensing, and machine learning to reduce required resources and dynamically allocate them with low overheads. This article provides a signal processing perspective of mmWave JRC systems with an emphasis on waveform design.
Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). First posted on arXiv 2 May 2019.
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Citing papers per year: 2021: 2; 2022: 2; 2023: 2.
6 papers.
- 2021Terahertz-Band Joint Ultra-Massive MIMO Radar-Communications: Model-Based and Model-Free Hybrid Beamformingcited by 5
- 2021Federated Dropout Learning for Hybrid Beamforming With Spatial Path Index Modulation In Multi-User mmWave-MIMO Systemscited by 2
- 2022Beurling-Selberg Extremization for Dual-Blind Deconvolution Recovery in Joint Radar-Communicationscited by 1
- 2022Online Bayesian Meta-Learning for Cognitive Tracking Radarcited by 0
- 2023Multi-Antenna Dual-Blind Deconvolution for Joint Radar-Communications via SoMAN Minimizationcited by 0
- 2023Sparse Array Design for Direction Finding using Deep Learningcited by 0
- 2023Sparse Array Design for Direction Finding using Deep Learning8 Aug 2023
- 2023Multi-Antenna Dual-Blind Deconvolution for Joint Radar-Communications via SoMAN Minimization23 Mar 2023
- 2022Beurling-Selberg Extremization for Dual-Blind Deconvolution Recovery in Joint Radar-Communications16 Nov 2022
- 2022Online Bayesian Meta-Learning for Cognitive Tracking Radar7 Jul 2022
- 2021Terahertz-Band Joint Ultra-Massive MIMO Radar-Communications: Model-Based and Model-Free Hybrid Beamforming27 Feb 2021
- 2021Federated Dropout Learning for Hybrid Beamforming With Spatial Path Index Modulation In Multi-User mmWave-MIMO Systems15 Feb 2021