Bayesian Predictive Beamforming for Vehicular Networks: A Low-Overhead Joint Radar-Communication Approach

The development of dual-functional radar-communication (DFRC) systems, where vehicle localization and tracking can be combined with vehicular communication, will lead to more efficient future vehicular networks. In this paper, we develop a predictive beamforming scheme in the context of DFRC systems...

Full description

Saved in:
Bibliographic Details
Published in:IEEE transactions on wireless communications 2021-03, Vol.20 (3), p.1442-1456
Main Authors: Yuan, Weijie, Liu, Fan, Masouros, Christos, Yuan, Jinhong, Ng, Derrick Wing Kwan, Gonzalez-Prelcic, Nuria
Format: Article
Language:English
Subjects:
Algorithms
Array signal processing
beam tracking
Beamforming
Communication
Complexity
Dual-functional radar-communication
Echoes
Estimation
factor graph
Feedback
Message passing
OFDM
Parameter estimation
Radar tracking
Tracking
Vehicles
vehicular networks
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:The development of dual-functional radar-communication (DFRC) systems, where vehicle localization and tracking can be combined with vehicular communication, will lead to more efficient future vehicular networks. In this paper, we develop a predictive beamforming scheme in the context of DFRC systems. We consider a system model where the road-side unit estimates and predicts the motion parameters of vehicles based on the echoes of the DFRC signal. Compared to the conventional feedback-based beam tracking approaches, the proposed method can reduce the signaling overhead and improve the accuracy of the angle estimation. To accurately estimate the motion parameters of vehicles in real-time, we propose a novel message passing algorithm based on factor graph, which yields a near optimal performance achieved by the maximum a posteriori estimation. The beamformers are then designed based on the predicted angles for establishing the communication links. With the employment of appropriate approximations, all messages on the factor graph can be derived in a closed-form, thus reduce the complexity. Simulation results show that the proposed DFRC based beamforming scheme is superior to the feedback-based approach in terms of both estimation and communication performance. Moreover, the proposed message passing algorithm achieves a similar performance of the high-complexity particle filtering-based methods.
ISSN:1536-1276
1558-2248
DOI:10.1109/TWC.2020.3033776