Radar-Assisted Predictive Beamforming for Vehicular Links: Communication Served by Sensing
In vehicular networks of the future, sensing and communication functionalities will be intertwined. In this article, we investigate a radar-assisted predictive beamforming design for vehicle-to-infrastructure (V2I) communication by exploiting the dual-functional radar-communication (DFRC) technique....
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| Published in | IEEE transactions on wireless communications Vol. 19; no. 11; pp. 7704 - 7719 |
|---|---|
| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
| Published |
New York
IEEE
01.11.2020
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1536-1276 1558-2248 |
| DOI | 10.1109/TWC.2020.3015735 |
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| Abstract | In vehicular networks of the future, sensing and communication functionalities will be intertwined. In this article, we investigate a radar-assisted predictive beamforming design for vehicle-to-infrastructure (V2I) communication by exploiting the dual-functional radar-communication (DFRC) technique. Aiming for realizing joint sensing and communication functionalities at road side units (RSUs), we present a novel extended Kalman filtering (EKF) framework to track and predict kinematic parameters of each vehicle. By exploiting the radar functionality of the RSU we show that the communication beam tracking overheads can be drastically reduced. To improve the sensing accuracy while guaranteeing the downlink communication sum-rate, we further propose a power allocation scheme for multiple vehicles. Numerical results have shown that the proposed DFRC based beam tracking approach significantly outperforms the communication-only feedback based technique in the tracking performance. Furthermore, the designed power allocation method is able to achieve a favorable performance trade-off between sensing and communication. |
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| AbstractList | In vehicular networks of the future, sensing and communication functionalities will be intertwined. In this article, we investigate a radar-assisted predictive beamforming design for vehicle-to-infrastructure (V2I) communication by exploiting the dual-functional radar-communication (DFRC) technique. Aiming for realizing joint sensing and communication functionalities at road side units (RSUs), we present a novel extended Kalman filtering (EKF) framework to track and predict kinematic parameters of each vehicle. By exploiting the radar functionality of the RSU we show that the communication beam tracking overheads can be drastically reduced. To improve the sensing accuracy while guaranteeing the downlink communication sum-rate, we further propose a power allocation scheme for multiple vehicles. Numerical results have shown that the proposed DFRC based beam tracking approach significantly outperforms the communication-only feedback based technique in the tracking performance. Furthermore, the designed power allocation method is able to achieve a favorable performance trade-off between sensing and communication. |
| Author | Liu, Fan Yuan, Weijie Masouros, Christos Yuan, Jinhong |
| Author_xml | – sequence: 1 givenname: Fan orcidid: 0000-0002-5299-9317 surname: Liu fullname: Liu, Fan email: fan.liu@ucl.ac.uk organization: Department of Electronic and Electrical Engineering, University College London, London, U.K – sequence: 2 givenname: Weijie orcidid: 0000-0002-2158-0046 surname: Yuan fullname: Yuan, Weijie email: weijie.yuan@unsw.edu.au organization: School of Electrical Engineering and Telecommunications, University of New South Wales, Sydney, NSW, Australia – sequence: 3 givenname: Christos orcidid: 0000-0002-8259-6615 surname: Masouros fullname: Masouros, Christos email: chris.masouros@ieee.org organization: Department of Electronic and Electrical Engineering, University College London, London, U.K – sequence: 4 givenname: Jinhong orcidid: 0000-0002-5794-493X surname: Yuan fullname: Yuan, Jinhong email: j.yuan@unsw.edu.au organization: School of Electrical Engineering and Telecommunications, University of New South Wales, Sydney, NSW, Australia |
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| SubjectTerms | Antenna arrays Array signal processing beam alignment Beamforming Communication Downlink Kalman filtering Kalman filters power allocation Radar Radar tracking radar-communication Resource management Roadsides Sensors Tracking V2X Vehicles |
| Title | Radar-Assisted Predictive Beamforming for Vehicular Links: Communication Served by Sensing |
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