Localization MSE Analysis for Cooperative OFDM-ISAC

This paper develops a receiver-specific mean-squared-error (MSE) framework for cooperative integrated sensing and communication (ISAC) localization using random orthogonal frequency-division multiplexing (OFDM) payloads. It captures local peak perturbations and incorrect ambiguity-peak acquisition for two classical receiver processing schemes: matched filtering (MF) and reciprocal filtering (RF). For scatterers well separated in delay, we quantify how frequency spread and interference induced by symbol-energy fluctuations affect local delay errors under MF. RF removes symbol-dependent weighting but amplifies noise for low-energy symbols. Payload-conditioned joint Gaussian delay profiles yield peak-selection probabilities, which combine with nonlinear multistatic fusion errors to approximate position MSE while accounting for network geometry. Numerical results illustrate receiver-dependent estimation errors and the benefits of frequency-dependent constellation allocation.

Authors

Publication Details

Journal
arXiv (Cornell University)
Published
2026-11-02
DOI
https://doi.org/10.48550/arxiv.2611.02783
Primary Topic
Radar Systems and Signal Processing
Type
preprint
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preprint

Localization MSE Analysis for Cooperative OFDM-ISAC

Christos Masouros, Kaitao Meng, Kawon Han
arXiv (Cornell University)
Radar Systems and Signal Processing
preprint

Localization MSE Analysis for Cooperative OFDM-ISAC

Christos Masouros, Kaitao Meng, Kawon Han
preprint en

Abstract

This paper develops a receiver-specific mean-squared-error (MSE) framework for cooperative integrated sensing and communication (ISAC) localization using random orthogonal frequency-division multiplexing (OFDM) payloads. It captures local peak perturbations and incorrect ambiguity-peak acquisition for two classical receiver processing schemes: matched filtering (MF) and reciprocal filtering (RF). For scatterers well separated in delay, we quantify how frequency spread and interference induced by symbol-energy fluctuations affect local delay errors under MF. RF removes symbol-dependent weighting but amplifies noise for low-energy symbols. Payload-conditioned joint Gaussian delay profiles yield peak-selection probabilities, which combine with nonlinear multistatic fusion errors to approximate position MSE while accounting for network geometry. Numerical results illustrate receiver-dependent estimation errors and the benefits of frequency-dependent constellation allocation.

arXiv (Cornell University)
Radar Systems and Signal Processing
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