Sensing Mutual Information for Communication Signal with Deterministic Pilots and Random Data Payloads
Lei Xie, Hengtao He, Jun Tong, Fan Liu, Shenghui Song

TL;DR
This paper develops a theoretical framework for sensing mutual information in hybrid communication signals with pilots and data, optimizing precoding to enhance sensing capabilities while maintaining communication performance.
Contribution
It derives a closed-form expression for sensing mutual information using random matrix theory and proposes an efficient precoding optimization method for hybrid signals.
Findings
Theoretical SMI expression accurately matches simulations.
Proposed precoding outperforms benchmark schemes.
Enhanced sensing performance without compromising communication rate.
Abstract
The recent emergence of the integrated sensing and communication (ISAC) framework has sparked significant interest in quantifying the sensing capabilities inherent in communication signals. However, existing literature has mainly focused on scenarios involving either purely random or purely deterministic waveforms. This overlooks a critical reality: operational communication standards invariably utilize a hybrid structure comprising both deterministic pilots for channel estimation and random payloads for data transmission. To bridge this gap, this paper investigates the sensing mutual information (SMI) and precoding design specifically for ISAC systems employing communication signals with both pilots and data payloads. First, by utilizing random matrix theory (RMT), we derive a tractable closed-form expression for the SMI that accurately accounts for the statistical properties of the…
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Taxonomy
TopicsDistributed Sensor Networks and Detection Algorithms · Radar Systems and Signal Processing · Direction-of-Arrival Estimation Techniques
