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This paper investigates an intelligent reflecting surface (IRS) enabledmultiuser integrated sensing and communication (ISAC) system, which consists ofone multi-antenna base station (BS), one IRS, multiple single-antennacommunication users (CUs), and one extended target at the non-line-of-sight(NLoS) region of the BS. The IRS is deployed to not only assist thecommunication from the BS to the CUs, but also enable the BS's NLoS targetsensing based on the echo signals from the BS-IRS-target-IRS-BS link. Toprovide full degrees of freedom for sensing, we suppose that the BS sendsadditional dedicated sensing signals combined with the information signals.Accordingly, we consider two types of CU receivers, namely Type-I and Type-IIreceivers, which do not have and have the capability of cancelling theinterference from the sensing signals, respectively. Under this setup, wejointly optimize the transmit beamforming at the BS and the reflectivebeamforming at the IRS to minimize the Cram\'er-Rao bound (CRB) for estimatingthe target response matrix with respect to the IRS, subject to the minimumsignal-to-interference-plus-noise ratio (SINR) constraints at the CUs and themaximum transmit power constraint at the BS. We present efficient algorithms tosolve the highly non-convex SINR-constrained CRB minimization problems, byusing the techniques of alternating optimization and semi-definite relaxation.Numerical results show that the proposed design achieves lower estimation CRBthan other benchmark schemes, and the sensing signal interferencepre-cancellation is beneficial when the number of CUs is greater than one.

Cram\'er-Rao Bound Minimization for IRS-Enabled Multiuser Integrated Sensing and Communication with Extended Target