Semi-Passive Intelligent Reflecting Surface Enabled Sensing Systems
arxiv(2024)
摘要
Intelligent reflecting surface (IRS) has garnered growing interest and
attention due to its potential for facilitating and supporting wireless
communications and sensing. This paper studies a semi-passive IRS-enabled
sensing system, where an IRS consists of both passive reflecting elements and
active sensors. Our goal is to minimize the Cramér-Rao bound (CRB) for
parameter estimation under both point and extended target cases. Towards this
goal, we begin by deriving the CRB for the direction-of-arrival (DoA)
estimation in closed-form and then theoretically analyze the IRS reflecting
elements and sensors allocation design based on the CRB under the point target
case with a single-antenna base station (BS). To efficiently solve the
corresponding optimization problem for the case with a multi-antenna BS, we
propose an efficient algorithm by jointly optimizing the IRS phase shifts and
the BS beamformers. Under the extended target case, the CRB for the target
response matrix (TRM) estimation is minimized via the optimization of the BS
transmit beamformers. Moreover, we explore the influence of various system
parameters on the CRB and compare these effects to those observed under the
point target case. Simulation results show the effectiveness of the
semi-passive IRS and our proposed beamforming design for improving the
performance of the sensing system.
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