Pilot-Based SFO Estimation for Bistatic Integrated Sensing and Communication
Lucas Giroto de Oliveira, Yueheng Li, Silvio Mandelli, David Brunner,, Marcus Henninger, Xiang Wan, Tie Jun Cui, Thomas Zwick, and Benjamin Nuss

TL;DR
This paper introduces TITO, a pilot-based algorithm for accurate SFO estimation in OFDM ISAC systems, improving radar image quality by mitigating SFO effects, especially in non-line-of-sight scenarios with RIS assistance.
Contribution
The paper presents a novel TITO algorithm for SFO estimation in OFDM ISAC, utilizing pilot subcarriers and RIS to enhance accuracy and robustness over existing methods.
Findings
TITO achieves higher SFO estimation accuracy in simulations.
Experimental results at 26.2 GHz validate TITO's robustness.
TITO outperforms existing algorithms in non-line-of-sight scenarios.
Abstract
Enabling bistatic radar sensing within the context of integrated sensing and communication (ISAC) for future sixth generation mobile networks demands strict synchronization accuracy, which is particularly challenging to be achieved with over-the-air synchronization. Existing algorithms handle time and frequency offsets adequately, but provide insufficiently accurate sampling frequency offset (SFO) estimates that result in degradation of obtained radar images in the form of signal-to-noise ratio loss and migration of range and Doppler shift. This article introduces an SFO estimation algorithm named tilt inference of time offset (TITO) for orthogonal frequency-division multiplexing (OFDM)-based ISAC. Using available pilot subcarriers, TITO obtains channel impulse response estimates and extracts information on the SFO-induced delay migration to a dominant reference path with constant…
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Taxonomy
TopicsDistributed Sensor Networks and Detection Algorithms · Target Tracking and Data Fusion in Sensor Networks
