Cramér-Rao Bound Minimization for a Passive Sensing Multi-ISAC System

Jian Chen, Qikai Chen, Yansha Deng, Jie Jia*, Baoxin Yin, Xingwei Wang

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

The integrated sensing and communication (ISAC) system can simultaneously provide communication and radar sensing, effectively improving spectrum utilization. However, existing research mainly focuses on the mono-static sensing ISAC system, which has shortcomings in limited sensing range and accuracy. We thus investigate a passive sensing multi-ISAC system with multiple communication users and sensing targets, and consider two cases for multi-target sensing without and with prior target knowledge at the base stations (BSs), in which the BSs are interested in estimating the targets' response matrix and channel coefficients, respectively. We also formulate a joint beamforming problem to minimize the Cramér-Rao bound (CRB) of the worst estimation constrained by communication requirements, and obtain the optimal solution with semidefinite relaxation (SDR) assisted transformation. To verify the advantages of our proposed scheme, we consider the bi-static BSs system (B-B) and beamforming with sensing interference cancellation (W-S) as two benchmark schemes. Numerical results illustrate that the proposed scheme obtains better sensing performance and effectively alleviates the effect caused by sensing interference.

Original languageEnglish
JournalIEEE Transactions on Vehicular Technology
DOIs
Publication statusAccepted/In press - 2025

Keywords

  • Cramér-Rao bound
  • ISAC
  • joint beamforming
  • passive sensing

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