# An Overview of Signal Processing Techniques for Joint Communication and Radar Sensing

arXiv: https://arxiv.org/abs/2102.12780 · HTML: https://mlsanity.com/paper/2102.12780/

## Key facts

- Cited by 20 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 25 Feb 2021.

## Built on by (most cited first, 20 of 20)

- [DeepSense 6G: A Large-Scale Real-World Multi-Modal Sensing and Communication Dataset](https://mlsanity.com/paper/2211.09769/) (2022)
- [ISAC-NET: Model-driven Deep Learning for Integrated Passive Sensing and Communication](https://mlsanity.com/paper/2307.15074/) (2023)
- [Joint Sensing and Task-Oriented Communications with Image and Wireless Data Modalities for Dynamic Spectrum Access](https://mlsanity.com/paper/2312.13931/) (2023)
- [Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities](https://mlsanity.com/paper/2509.06968/) (2025)
- [Attention-Refined Unrolling for Sparse Sequential micro-Doppler Reconstruction](https://mlsanity.com/paper/2306.14233/) (2023)
- [Towards SISO Bistatic Sensing for ISAC](https://mlsanity.com/paper/2508.12614/) (2025)
- [Multimodal Mixture-of-Experts for ISAC in Low-Altitude Wireless Networks](https://mlsanity.com/paper/2512.01750/) (2025)
- [Variational Quantum Integrated Sensing and Communication](https://mlsanity.com/paper/2511.16597/) (2025)
- [Autoencoder-Based Parameter Estimation for Superposed Multi-Component Damped Sinusoidal Signals](https://mlsanity.com/paper/2604.03985/) (2026)
- [Multi-Point Integrated Sensing and Communication: Fusion Model and Functionality Selection](https://mlsanity.com/paper/2208.07592/) (2022)
- [Interference and noise cancellation for joint communication radar (JCR) system based on contextual information](https://mlsanity.com/paper/2302.06786/) (2023)
- [Multi-Base Station Cooperative Sensing with AI-Aided Tracking](https://mlsanity.com/paper/2310.20403/) (2023)
- [Deep Learning-based Target-To-User Association in Integrated Sensing and Communication Systems](https://mlsanity.com/paper/2401.12801/) (2024)
- [Task-Based Quantizer Design for Sensing With Random Signals](https://mlsanity.com/paper/2403.11187/) (2024)
- [Robust Egoistic Rigid Body Localization](https://mlsanity.com/paper/2501.10219/) (2025)
- [Efficient Beam Selection for ISAC in Cell-Free Massive MIMO via Digital Twin-Assisted Deep Reinforcement Learning](https://mlsanity.com/paper/2506.18560/) (2025)
- [Variational Secret Common Randomness Extraction](https://mlsanity.com/paper/2510.02048/) (2025)
- [AI-Empowered UAV-Assisted Backscatter Localization and ISAC for Zero-Energy IoT: A Comprehensive Survey](https://mlsanity.com/paper/2606.23125/) (2026)
- [AERIS: Offline Policy Improvement for Multi-UAV Integrated Sensing and Communication](https://mlsanity.com/paper/2608.25477/) (2026)
- [Parameter Estimation of Ringdown Quasinormal Modes with Autoencoder](https://mlsanity.com/paper/2609.14277/) (2026)

## Abstract (arXiv)

Joint communication and radar sensing (JCR) represents an emerging research field aiming to integrate the above two functionalities into a single system, sharing a majority of hardware and signal processing modules and, in a typical case, sharing a single transmitted signal. It is recognised as a key approach in significantly improving spectrum efficiency, reducing device size, cost and power consumption, and improving performance thanks to potential close cooperation of the two functions. Advanced signal processing techniques are critical for making the integration efficient, from transmission signal design to receiver processing. This paper provides a comprehensive overview of JCR systems from the signal processing perspective, with a focus on state-of-the-art. A balanced coverage on both transmitter and receiver is provided for three types of JCR systems, communication-centric, radar-centric, and joint design and optimization.