Zhang M, Su Y, Franchi N, Weigel R, Reißland T (2025)
Publication Language: English
Publication Type: Journal article, Online publication
Publication year: 2025
Book Volume: 13
Pages Range: 170395-170409
DOI: 10.1109/ACCESS.2025.3615453
Open Access Link: https://doi.org/10.1109/ACCESS.2025.3615453
Joint Communication and Sensing (JCAS) is a key enabler for future 6G networks, allowing data transmission and environmental sensing through shared spectral and hardware resources. To address challenges such as the sensing-communication trade-off, hardware limitations, and multi-user interference, we propose a scalable Multiple Input Multiple Output (MIMO) framework based on Uniform Rectangular Arrays (URA) with partially connected hybrid beamforming (PC-HBF). On the transmitter side, a fairness-aware beamforming optimization maximizes sensing gain while ensuring communication quality, solved via an Interior-Point Method (IPM) with adaptive initialization for improved convergence. At the receiver, a two-stage Block Orthogonal Matching Pursuit (Block-OMP) with Adaptive Dictionary Selection and Refinement (ADSR) enhances combining accuracy under hardware constraints while maintaining low complexity. For radar sensing, we introduce a hybrid direction-of-arrival (DoA) estimation method combining Beamscan and MUSIC algorithms. This design enables accurate angle estimation despite PC-HBF limitations, providing a practical sensing solution for JCAS scenarios. Simulation results demonstrate the practical effectiveness of our design: IPM-based beamforming converges within 15 iterations, ADSR-enhanced combining improves spectral efficiency by up to 1 dB over baseline OMP, approaching the performance of fully digital beamforming while supporting joint sensing, and the DoA method resolves targets spaced as closely as 5°. These gains underline the framework’s potential in real-world applications such as smart mobility and autonomous driving, enabling scalable and high-performance JCAS systems.
APA:
Zhang, M., Su, Y., Franchi, N., Weigel, R., & Reißland, T. (2025). Hybrid Beamforming for Multi-User Joint Communication and Sensing With URA Under Partially Connected Architectures. IEEE Access, 13, 170395-170409. https://doi.org/10.1109/ACCESS.2025.3615453
MLA:
Zhang, Mengyu, et al. "Hybrid Beamforming for Multi-User Joint Communication and Sensing With URA Under Partially Connected Architectures." IEEE Access 13 (2025): 170395-170409.
BibTeX: Download