IRS-Aided Non-Orthogonal ISAC Systems: Performance Analysis and Beamforming Design

TL;DR

This paper analyzes the performance trade-offs in IRS-aided non-orthogonal ISAC systems, proposing a unified CRLB-based framework and a joint beamforming algorithm to enhance simultaneous communication and sensing.

Contribution

It introduces a modified CRLB for non-orthogonal ISAC, derives closed-form expressions, and develops a joint beamforming design to optimize communication and sensing performance trade-offs.

Findings

IRS-aided NO-ISAC outperforms TD-ISAC in both communication and localization.

Random signals can achieve localization performance comparable to dedicated signals.

Increasing IRS elements significantly boosts system performance.

Abstract

Intelligent reflecting surface (IRS) has shown its effectiveness in facilitating orthogonal time-division integrated sensing and communications (TD-ISAC), in which the sensing task and the communication task occupy orthogonal time-frequency resources, while the role of IRS in the more interesting scenarios of non-orthogonal ISAC (NO-ISAC) systems has so far remained unclear. In this paper, we consider an IRS-aided NO-ISAC system, where a distributed IRS is deployed to assist concurrent communication and location sensing for a blind-zone user, occupying non-orthogonal/overlapped time-frequency resources. We first propose a modified Cramer-Rao lower bound (CRLB) to characterize the performances of both communication and location sensing in a unified manner. We further derive the closed-form expressions of the modified CRLB in our considered NO-ISAC system, enabling us to identify the fundamental trade-off between the communication and location sensing performances. In addition, by exploiting the modified CRLB, we propose a joint active and passive beamforming design algorithm that achieves a good communication and location sensing trade-off. Through numerical results, we demonstrate the superiority of the IRS-aided NO-ISAC systems over the IRS-aided TD-ISAC systems, in terms of both communication and localization performances. Besides, it is shown that the IRS-aided NO-ISAC system with random communication signals can achieve comparable localization performance to the IRS-aided localization system with dedicated positioning reference signals. Moreover, we investigate the trade-off between communication performance and localization performance and show how the performance of the NO-ISAC system can be significantly boosted by increasing the number of the IRS elements.