Kavli Affiliate: Feng Wang
| First 5 Authors: Chikun Liao, Feng Wang, Vincent K. N. Lau, ,
| Summary:
In this paper, we investigate an intelligent reflecting surface
(IRS)-assisted integrated sensing and communication (ISAC) system design in a
clutter environment. Assisted by an IRS equipped with a uniform linear array
(ULA), a multi-antenna base station (BS) is targeted for communicating with
multiple communication users (CUs) and sensing multiple targets simultaneously.
We consider the IRS-assisted ISAC design in the case with Type-I or Type-II
CUs, where each Type-I and Type-II CU can and cannot cancel the interference
from sensing signals, respectively. In particular, we aim to maximize the
minimum sensing beampattern gain among multiple targets, by jointly optimizing
the BS transmit beamforming vectors and the IRS phase shifting matrix, subject
to the signal-to-interference-plus-noise ratio (SINR) constraint for each
Type-I/Type-II CU, the interference power constraint per clutter, the
transmission power constraint at the BS, and the cross-correlation pattern
constraint. Due to the coupling of the BS’s transmit design variables and the
IRS’s phase shifting matrix, the formulated max-min IRS-assisted ISAC design
problem in the case with Type-I/Type-II CUs is highly non-convex. As such, we
propose an efficient algorithm based on the alternating-optimization and
semi-definite relaxation (SDR) techniques. In the case with Type-I CUs, we show
that the dedicated sensing signal at the BS is always beneficial to improve the
sensing performance. By contrast, the dedicated sensing signal at the BS is not
required in the case with Type-II CUs. Numerical results are provided to show
that the proposed IRS-assisted ISAC design schemes achieve a significant gain
over the existing benchmark schemes.
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