  In this paper, we propose a novel symbol-level precoding (SLP) method for a
multi-user multi-input multi-output (MU-MIMO) downlink Integrated Sensing and
Communications (ISAC) system based on faster-than-Nyquist (FTN) signaling. Our
method minimizes the minimum mean squared error (MMSE) for target parameter
estimation while guaranteeing per-user quality-of-service by exploiting
constructive interference (CI) techniques. We tackle the non-convex problem
using an efficient successive convex approximation (SCA) method. Numerical
results demonstrate that our FTN-ISAC-SLP design significantly outperforms
conventional benchmarks in both communication and sensing performance.
