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Integrated sensing and communication has emerged as a transformative technology for future wireless communication networks, enabling the simultaneous realization of radar sensing and communication functions by sharing available resources. To fully exploit the available spatial degrees of freedom in monostatic ISAC systems, we propose a dynamic array partitioning architecture that allows the base station to allocate antennas for transmitting dual-functional signals and receiving the corresponding echoes. Based on this architecture, we jointly design the transmit beamforming and array partitioning to minimize the Cram´er-Rao bound (CRB) for target directionof- arrival estimation, while ensuring compliance with signalto- interference-plus-noise ratio requirements for multiuser communication, power budget constraints, and array partitioning limitations. To address the resulting optimization problem, we develop an alternating algorithm leveraging alternating direction method of multipliers and semi-definite relaxation. Simulation results demonstrate that the proposed joint array partitioning and beamforming design significantly improves the CRB and the resulting DOA estimation performance.
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This content will become publicly available on May 3, 2026
CRB Optimization Using a Parametric Scattering Model for Extended Targets in ISAC Systems
This paper presents a novel parametric scattering model (PSM) for sensing extended targets in integrated sensing and communication (ISAC) systems. The PSM addresses the limitations of traditional models by efficiently capturing the target’s angular characteristics through a compact set of key parameters, including the central angle and angular spread, enabling efficient optimization. Based on the PSM, we first derive the Cram´er-Rao bound (CRB) for parameter estimation and then propose a beamforming design algorithm to minimize the CRB while meeting both communication signal-to-interference-plusnoise ratio (SINR) and power constraints. By integrating the PSM into the beamforming optimization process, the proposed framework achieves superior CRB performance while balancing the tradeoff between sensing accuracy and communication quality. Simulation results demonstrate that the PSM-based approach consistently outperforms traditional unstructured and discrete scattering models, particularly in resource-limited scenarios, highlighting its practical applicability and scalability.
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- PAR ID:
- 10643381
- Publisher / Repository:
- IEEE
- Date Published:
- Page Range / eLocation ID:
- 1 to 6
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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