mlsanityData to 14 Oct 2026

Joint Radar and Communication Design: Applications, State-of-the-art, and the Road Ahead

arXiv 1906.00789 ↗First posted 3 Jun 2019eess.SPcited by 19

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Abstract (arXiv)

In this paper, we firstly overview the application scenarios and the research progress in the area of communication and radar spectrum sharing (CRSS). We then propose a novel transceiver architecture and frame structure for a dual-functional radar-communication (DFRC) base station (BS) operating in the millimeter wave (mmWave) band, using the hybrid analog-digital (HAD) beamforming technique. We assume that the BS is serving a multi-antenna aided user equipment (UE) operating in a mmWave channel, which in the meantime actively detects multiple targets. Note that part of the targets also play the role of scatterers for the communication signal. Given this framework, we propose a novel scheme for joint target search and communication channel estimation relying on the omni-directional pilot signals generated by the HAD structure. Given a fully-digital communication precoder and a desired radar transmit beampattern, we propose to design the analog and digital precoders under non-convex constant-modulus (CM) and power constraints, such that the BS can formulate narrow beams towards all the targets, while pre-equalizing the impact of the communication channel. Furthermore, we design an HAD receiver that can simultaneously process signals from the UE and echo waves from the targets. By tracking the angular variation of the targets, we show that it is possible to recover the target echoes and mitigate the potential interference imposed on the UE signals by invoking the successive interference cancellation (SIC) technique, even when the radar and communication signals share the equivalent signal-to-noise ratio (SNR). The feasibility and the efficiency of the proposed approaches in realizing DFRC are verified via numerical simulations. Finally, our discussions are summarized by overviewing the open problems in the research field of CRSS.

Key facts. Cited by 19 papers in the map (data through 14 Oct 2026). First posted on arXiv 3 Jun 2019.

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Citing papers per year: 2021: 3; 2022: 0; 2023: 2; 2024: 4; 2025: 1; 2026: 9.

19 papers.

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  1. 2024A Survey on Integrated Sensing, Communication, and Computationcited by 12
  2. 2021Wireless Sensing With Deep Spectrogram Network and Primitive Based Autoregressive Hybrid Channel Modelcited by 9
  3. 2021Terahertz-Band Joint Ultra-Massive MIMO Radar-Communications: Model-Based and Model-Free Hybrid Beamformingcited by 5
  4. 2021Constrained Contextual Bandit Learning for Adaptive Radar Waveform Selectioncited by 5
  5. 2023Task-Oriented Integrated Sensing, Computation and Communication for Wireless Edge AIcited by 4
  6. 2024Deep-Learning Channel Estimation for IRS-Assisted Integrated Sensing and Communication Systemcited by 2
  7. 2024Deep-Learning-Based Channel Estimation for IRS-Assisted ISAC Systemcited by 1
  8. 2024Extreme Learning Machine-based Channel Estimation in IRS-Assisted Multi-User ISAC Systemcited by 1
  9. 2026QuaMoE-DRF: Proactive Beam and Rate Adaptation via Multimodal Dynamic Radio Map Forecasting in ISAC Networkscited by 1
  10. 2023Interference and noise cancellation for joint communication radar (JCR) system based on contextual informationcited by 0
  11. 2025Dim and Small Target Detection for Drone Broadcast Frames Based on Time-Frequency Analysiscited by 0
  12. 2026Deep Learning-Driven Friendly Jamming for Secure Multicarrier ISAC Under Channel Uncertaintycited by 0
7 more
  1. 2026AI-Empowered UAV-Assisted Backscatter Localization and ISAC for Zero-Energy IoT: A Comprehensive Surveycited by 0
  2. 2026Task-Oriented Candidate-Latent Feedback for Coarse-to-Fine Sensing in Distributed OFDM-ISAC Networkscited by 0
  3. 2026AERIS: Offline Policy Improvement for Multi-UAV Integrated Sensing and Communicationcited by 0
  4. 2026Sense Once, Serve Many: Common-Trace Factorized Constrained PPO for Online Sensing-Session Consolidation in Multi-Tenant ISAC Networkscited by 0
  5. 2026StarBOA: Real-Time Mamba State-Space Unrolling for Sparse Radar Micro-Doppler in ISAC Networkscited by 0
  6. 2026Short-Length Code Designs for Integrated Sensing and Communications: A Deep Learning Approachcited by 0
  7. 2026Comparative Evaluation of Deep-Learning based DoA Estimators for Real-Time ISAC Beamformingcited by 0