Work

Optimized Beamforming for Joint Bistatic Positioning and Monostatic Sensing

Year: 2025

Type: conference-paper

Abstract: We investigate the performance tradeoff between bistatic positioning (BP) and monostatic sensing (MS) in a multi-input multi-output orthogonal frequency division multiplexing scenario. We derive the Cramér-Rao bounds (CRBs) for BP at the user equipment and MS at the base station. To balance these objectives, we propose a multi-objective optimization framework that optimizes beamformers using a weighted-sum CRB approach, ensuring the weak Pareto boundary. We also introduce two mismatch-minimizing approaches, targeting beamformer mismatch and variance matrix mismatch, and solve them distinctly. Numerical results demonstrate the performance tradeoff between BP and MS, revealing significant gains with the proposed methods and highlighting the advantages of minimizing the weighted-sum mismatch of variance matrices.

Source: IEEE International Conference on Communications workshops

DOI: 10.1109/iccworkshops67674.2025.11162149

Authors: Yuchen Zhang, Hui Chen, Pinjun Zheng, Boyu Ning, Henk Wymeersch, Tareq Y. Al-Naffouri

Institutions: King Abdullah University of Science and Technology, Chalmers University of Technology, University of British Columbia, University of Electronic Science and Technology of China

Language: English

Topic: Radar Systems and Signal Processing

Subfield: Aerospace Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: green

Funders: King Abdullah University of Science and Technology, Vetenskapsrådet, HORIZON EUROPE Framework Programme

Award: Hardware-aware Integrated Localization and Sensing for Communication Systems