Symbol-Level Precoding for Integrated Sensing and Communications: A Faster-Than-Nyquist Approach
Zihan Liao, Fan Liu
Abstract
In this letter, 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.
Topics & Concepts
PrecodingTelecommunications linkComputer scienceMIMONyquist–Shannon sampling theoremInterference (communication)ConstructiveCommunications systemConvex optimizationAlgorithmSingle antenna interference cancellationTelecommunicationsRegular polygonMathematicsDecoding methodsGeometryOperating systemComputer visionChannel (broadcasting)Process (computing)Advanced Power Amplifier DesignAdvanced MIMO Systems OptimizationPAPR reduction in OFDM