Joint Waveform and Discrete Phase Shift Design for RIS-Assisted Integrated Sensing and Communication System Under Cramer-Rao Bound Constraint

Abstract

This paper studies an integrated sensing and communication (ISAC) system, where a multi-antenna base station transmits beamformed signals for joint downlink multi-user communication and radar sensing of an extended target (ET). By considering echo signals as reflections from valid elements on the ET contour, a set of novel Cramér-Rao bounds (CRBs) is derived for parameter estimation of the ET, including central range, direction, and orientation. The ISAC transmit beamforming design is then formulated as an optimization problem, aiming to minimize the CRB associated with radar sensing, while satisfying a minimum signal-to-interference-pulse-noise ratio requirement for each communication user, along with a 3-dB beam coverage constraint tailored for the ET. To solve this non-convex problem, we utilize semidefinite relaxation (SDR) and propose a rank-one solution extraction scheme for non-tight relaxation circumstances. To reduce the computation complexity, we further employ an efficient zero-forcing (ZF) based beamforming design, where the sensing task is performed in the null space of communication channels. Numerical results validate the effectiveness of the obtained CRB, revealing the diverse features of CRB for differently shaped ETs. The proposed SDR beamforming design outperforms benchmark designs with lower estimation error and CRB, while the ZF beamforming design greatly improves computation efficiency with minor sensing performance loss.

The Rise of Intelligent Reflecting Surfaces in Integrated Sensing and Communications Paradigms

“…Codebook-based design for IRS phase-shifts MSE of the target direction cosine vector ISAC [10] DFRC (single user, single target) SDR and Bisection search for transmit beamforming; majority-minimization for IRS design SNR at the radar receiver ISAC [11] DFRC (single user, multi-target) Alternating optimization of transmit beamformer and the IRS phase shifts via SDR IRS beampattern gain with communications SNR constraint ISAC [12] Wideband DFRC (single target, multi-user) SDR for transmit beamforming; ADMM for IRS design Average radar SINR plus communications SINR ISAC [13] Wideband DFRC with multiple IRSs (single target, multi-user) Dinkelbach's method for transmit beamforming; ADMM for IRS design Average radar SINR plus communications SINR ISAC [14] DFRC with quantized IRS phases (multi-user, multi-target)…”

“…4) Interference Suppression: The passive IRS beamforming is useful to suppress the interference from coexisting emitters while maintaining a satisfactory radar performance [14]. As shown in Fig.…”

“…1). While IRS-assisted communications in ISAC yields higher spectral/energy efficiency, the IRS-assisted radar in ISAC improves target detection performance [10,14]. Furthermore, the IRS may be used by either of the systems in time-multiplexed manner requiring a trade-off between radar and communications performances depending on the application.…”

“…The trade-off between the accuracy/importance of both radar and communications tasks is usually controlled with a tuning parameter in most of the existing IRS-assisted ISAC systems (see, e.g., Table I). The tuning parameter is usually selected between 0 (radar-only design) and 1 (communications-only design) [3] to optimize the balance over the performance metrics related to both radar and communications, such as the signal-to-interference-plusnoise-ratio (SINR) [10], Cramer-Rao lower bound (CRLB) of target direction-of-arrivals (DoAs) [14], IRS beampattern gain [11], MSE of the communications symbols [13,14] and the MSE of target direction vector [9]. The optimization process is rather straightforward in narrowband communications [4] and radar [6].…”

Joint Beamforming and Reflection Design for RIS-assisted ISAC Systems

“…Inspired by this flexibility, research on deploying RIS in ISAC systems has appeared in recent years. The authors in [8] and [9] studied the employment of RIS to mitigate multi-user interference (MUI) and ensure radar sensing performance in terms of beampattern and Cramér-Rao bound. In [10], the signal-to-noise ratio (SNR) metric was utilized to evaluate the performance of an RIS-aided single-user system.…”