Cram\'er-Rao Bound Analysis of Bistatic ISAC Under Partial Symbol Knowledge and Clutter

TL;DR

This paper analyzes the sensing performance of bistatic ISAC systems under partial symbol knowledge and clutter using CRB, highlighting the impact of symbol uncertainty and clutter on estimation accuracy.

Contribution

It introduces a CRB analysis considering partial symbol knowledge and clutter, deriving a correlation aware channel estimator and evaluating its performance.

Findings

CRB degradation increases with clutter and symbol uncertainty.

The proposed channel estimator outperforms conventional block fading methods.

Symbol knowledge level significantly affects sensing and spectral efficiency.

Abstract

Integrated sensing and communication (ISAC) systems rely on communication waveforms to perform sensing tasks, thus making their sensing performance strongly dependent on the level of communication symbol knowledge available to the sensing receivers. However, the existing literature fails to capture this dependency, often relying on full symbol knowledge assumptions. In this paper, we present a Cramer Rao bound (CRB) analysis of a bistatic ISAC network with heterogeneous uplink and downlink illumination and structured clutter. We consider different symbol knowledge regimes by modeling unknown communication symbols as nuisance parameters. Assuming a temporal evolution of the communication channel, we derive a correlation aware channel estimator and an expression for the UEs uplink spectral efficiency (SE). Numerical results show the CRB degradation induced by clutter and symbol uncertainty and how this can affect resource allocation policies. We also show the performance gain of our channel estimator relative to conventional block fading architectures.