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

By Weijie Yuan, Fan Liu, Christos Masouros, Jinhong Yuan, Derrick Wing Kwan Ng, Nuria González-Prelcic. IEEE Transactions on Wireless Communications, 2020

309 citations recorded by the source corpus.

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.

Subfields: Aerospace Engineering, Signal Processing

View Paper: https://www.semanticscholar.org/paper/cb492b1b3900cb57441c9ddf0e1ba8b875d00201

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Citations in the corpus

Integrated Sensing and Communications: Toward Dual-Functional Wireless Networks for 6G and Beyond (2021, methodology): “More importantly, the wireless sensing functionality equipped on the RSU provides an alternative way to acquire vehicles’ states in a fast and inexpensive manner, which in turn facilitates the Vehicle-to-Infrastructure (V2I) communications and platooning by significantly reducing the beam training o”
A Survey on Fundamental Limits of Integrated Sensing and Communication (2021, background): “For example, recently, there have been an increasing number of academic publications on ISAC, ranging from transceiver architecture and frame structure [3], [8], ISAC waveform design [9], [10], [11], joint coding design [12], [13], [14], temporal-spectral-spatial signal processing [15], [16], [17], ”
Enabling Joint Communication and Radar Sensing in Mobile Networks—A Survey (2020, background): “Current research has been limited to propagation path optimization [90], [97], [116], [117] and secure communications [118].”
Joint Maneuver and Beamforming Design for UAV-Enabled Integrated Sensing and Communication (2021, background): “, [3], [4], [5], [6], [7], [8], [9], [10]).”
On the Fundamental Tradeoff of Integrated Sensing and Communications Under Gaussian Channels (2022, background): “Nonetheless, the distinct physical roles of X and H in S&C and the resulting performance measures lead to a number of unique performance tradeoffs and design criteria [7]–[10] to the ISAC signal processing, particularly for simultaneously realizing S&C functionalities via a unified waveform.”
Integrated Sensing and Communication-Assisted Orthogonal Time Frequency Space Transmission for Vehicular Networks (2021, methodology): “In contrast, benefiting from ISAC signals, the RSU can extract the angular parameters from the reflected echoes [29], [30], which can be exploited by the RSU to predict the angles in the following time instant.”
An Overview of Signal Processing Techniques for Joint Communication and Radar Sensing (2021, unknown): “Examples are sensing assisted secure communications [45] and BF [46]–[49].”
The Integrated Sensing and Communication Revolution for 6G: Vision, Techniques, and Applications (2024, unknown): “In a similar setting, Yuan et al. [283] proposed a variation of this idea, exploiting the delay and Doppler parameters estimated at the BS for the link corresponding to a particular vehicle.”