Multipath Component-Enhanced Signal Processing for Integrated Sensing and Communication Systems

TL;DR

This paper introduces a novel MPC-enhanced signal processing scheme for integrated sensing and communication systems, enabling high-accuracy localization and velocity estimation of multiple targets in complex environments.

Contribution

It proposes a new MPC-based sensing scheme with symbol-level fusion and applies KRST coding to improve ISAC performance in scattering environments.

Findings

SL-MPS scheme outperforms existing methods in localization accuracy

The approach enables absolute velocity estimation with a single sensing attempt

Simulation results confirm robustness and improved accuracy

Abstract

Integrated sensing and communication (ISAC) has gained traction in academia and industry. Recently, multipath components (MPCs), as a type of spatial resource, have the potential to improve the sensing performance in ISAC systems, especially in richly scattering environments. In this paper, we propose to leverage MPC and Khatri-Rao space-time (KRST) code within a single ISAC system to realize high-accuracy sensing for multiple dynamic targets and multi-user communication. Specifically, we propose a novel MPC-enhanced sensing processing scheme with symbol-level fusion, referred to as the "SL-MPS" scheme, to achieve high-accuracy localization of multiple dynamic targets and empower the single ISAC system with a new capability of absolute velocity estimation for multiple targets with a single sensing attempt. Furthermore, the KRST code is applied to flexibly balance communication and sensing performance in richly scattering environments. To evaluate the contribution of MPCs, the closed-form Cram\'er-Rao lower bounds (CRLBs) of location and absolute velocity estimation are derived. Simulation results illustrate that the proposed SL-MPS scheme is more robust and accurate in localization and absolute velocity estimation compared with the existing state-of-the-art schemes.