Multibeam for Joint Communication and Radar Sensing Using Steerable Analog Antenna Arrays
By J. Andrew Zhang, Xiaojing Huang, Y. Guo, Jinhong Yuan, Robert W. Heath. IEEE Transactions on Vehicular Technology, 2018
321 citations recorded by the source corpus.
Beamforming has a great potential for joint communication and radar sensing (JCAS), which is becoming a demanding feature on many emerging platforms, such as unmanned aerial vehicles and smart cars. Although beamforming has been extensively studied for communication and radar sensing respectively, its application in the joint system is not straightforward due to different beamforming requirements by communication and sensing. In this paper, we propose a novel multibeam framework using steerable analog antenna arrays, which allows seamless integration of communication and sensing. Different to conventional JCAS schemes that support JCAS using a single beam, our framework is based on the key innovation of multibeam technology: providing fixed subbeam for communication and packet-varying scanning subbeam for sensing, simultaneously from a single transmitting array. We provide a system architecture and protocols for the proposed framework, complying well with modern packet communication systems with multicarrier modulation. We also propose low-complexity and effective multibeam design and generation methods, which offer great flexibility in meeting different communication and sensing requirements. We further develop sensing parameter estimation algorithms using conventional digital Fourier transform and one-dimensional compressive sensing techniques, matching well with the multibeam framework. Simulation results are provided and validate the effectiveness of our proposed framework, beamforming design methods, and the sensing algorithms.
Subfields: Aerospace Engineering, Computational Mechanics, Electrical and Electronic Engineering
View Paper: https://www.semanticscholar.org/paper/3579dae2eb61e148f6849a290a1e30faeb84f052
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Aerospace Engineering
- Jie Xu
- Rui Zhang
- Qingqing Wu
- Derrick Wing Kwan Ng
- Fan Liu
- Christos Masouros
- Robert Schober
- Yonina C. Eldar
In Computational Mechanics
- Christos Masouros
- Fan Liu
- Jie Xu
- Naofal Al-Dhahir
- Robert Schober
- Yonina C. Eldar
- Jinhong Yuan
- Yong Zeng
In Electrical and Electronic Engineering
- Rui Zhang
- Robert Schober
- Qingqing Wu
- Derrick Wing Kwan Ng
- Jie Xu
- Yong Zeng
- Naofal Al-Dhahir
- Lajos Hanzo
Citations in the corpus
- A Comprehensive Overview on 5G-and-Beyond Networks With UAVs: From Communications to Sensing and Intelligence (2020, methodology): “Beamforming for JCAS with analog or hybrid analog/digital antenna architectures was studied in [291] and [47], respecitvely.”
- Joint Radar and Communication Design: Applications, State-of-the-Art, and the Road Ahead (2019, background): “While the authors of [97] have presented analog beamforming designs for smallscale MIMO DFRC, little attention has been paid to HAD based massive MIMO (mMIMO) DFRC systems, which might be more practical, whilst maintaining compatibility with 5G mmWave applications.”
- An Overview of Signal Processing Techniques for Joint Communication and Radar Sensing (2021, unknown): “A good solution is the multibeam technology [23], [70], [71].”
- Integrated Sensing and Communication-Assisted Orthogonal Time Frequency Space Transmission for Vehicular Networks (2021, methodology): “To support all P vehicles, the RSU first prepares a multi-beam ISAC signal s ( t ) with P dimensions [37], i.e., where the i -th signal s i ( t ) carries the information to vehicle i .”
- Cramér-Rao Bound Optimization for Joint Radar-Communication Beamforming (2021, methodology): “Together with the use of mmWave and hybrid analog-digital beamforming techniques, the radar sensing functionality can be incorporated into the massive MIMO base station (BS) [16], [23], [24], which may be deployed in the 5G/B5G vehicular network as a road side unit (RSU) for both vehicular communica”
- Enabling Joint Communication and Radar Sensing in Mobile Networks—A Survey (2020, methodology): “Decomposed spatial precoder Multibeam optimization where two pre-generated sub-beams are optimally combined, to support fast varying scanning directions and multiple targets [29], [77], [134], [135].”
- Throughput Maximization for UAV-Enabled Integrated Periodic Sensing and Communication (2022, unknown): “Several similar terminologies have been utilized to describe this related research, such as radar-communication (RadCom) [7], [8], dual-functional radar communication (DFRC) [9], [10], joint communication and radar sensing (JCAS) [11], [12].”