Faster-Than-Nyquist Symbol-Level Precoding for Wideband Integrated Sensing and Communications

TL;DR

This paper introduces a novel symbol-level precoding method for wideband MU-MIMO ISAC systems using faster-than-Nyquist signaling, improving throughput and sensing accuracy.

Contribution

It develops a non-convex optimization framework for FTN-ISAC with constructive interference, solved via minorization and SCA techniques, advancing joint sensing and communication.

Findings

Enhanced communication throughput demonstrated

Satisfactory sensing performance maintained

Effective optimization strategies employed

Abstract

In this paper, we present an innovative symbol-level precoding (SLP) approach for a wideband multi-user multi-input multi-output (MU-MIMO) downlink Integrated Sensing and Communications (ISAC) system employing faster-than-Nyquist (FTN) signaling. Our proposed technique minimizes the minimum mean squared error (MMSE) for the sensed parameter estimation while ensuring the communication per-user quality-of-service through the utilization of constructive interference (CI) methodologies. While the formulated problem is non-convex in general, we tackle this issue using proficient minorization and successive convex approximation (SCA) strategies. Numerical results substantiate that our FTN-ISAC-SLP framework significantly enhances communication throughput while preserving satisfactory sensing performance.