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.
@article{arxiv.2302.13757,
title = {Symbol-Level Precoding for Integrated Sensing and Communications: A Faster-Than-Nyquist Approach},
author = {Zihan Liao and Fan Liu},
journal= {arXiv preprint arXiv:2302.13757},
year = {2023}
}