  A low-complexity design is proposed for an integrated sensing and
communication (ISAC) system aided by an intelligent reflecting surface (IRS).
The radar precoder and IRS parameter are computed alternatingly to maximize the
weighted sum signal-to-noise ratio (SNR) at the radar and communication
receivers. The IRS design problem has an objective function of fourth order in
the IRS parameter matrix, and is subject to highly non-convex unit modulus
constraints. To address this challenging problem and obtain a low-complexity
solution, we employ a minorization technique twice; the original fourth order
objective is first surrogated with a quadratic one via minorization, and is
then minorized again to a linear one. This leads to a closed form solution for
the IRS parameter in each iteration, thus reducing the IRS design complexity.
Numerical results are presented to show the effectiveness of the proposed
method.
