Position and Velocity Estimation Accuracy in MIMO-OFDM ISAC Networks: A Fisher Information Analysis

Fuente: arXiv
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Main Authors: Pucci, Lorenzo, Arcangeloni, Luca, Giorgetti, Andrea
Format: Preprint
Published: 2025
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author Pucci, Lorenzo
Arcangeloni, Luca
Giorgetti, Andrea
author_facet Pucci, Lorenzo
Arcangeloni, Luca
Giorgetti, Andrea
contents This paper presents a theoretical framework to derive information-theoretic bounds on the estimation accuracy of target position and velocity in orthogonal frequency division multiplexing (OFDM)-based integrated sensing and communication (ISAC) networks composed of multiple cooperative and distributed multiple-input multiple-output (MIMO) base stations (BSs). Leveraging Fisher information analysis, we derive closed-form expressions for the Cramér-Rao lower bounds (CRLBs) in both monostatic and bistatic configurations. The framework is then extended to cooperative settings, including networks with multiple coordinated monostatic sensors and multistatic configurations, enabling joint estimation of target position and velocity. We systematically examine how estimation accuracy depends on key system parameters such as the number of BSs, bandwidth, antenna configuration, and network geometry. Numerical results highlight the performance gains enabled by cooperative sensing and provide insights to guide the design of future ISAC systems.
format Preprint
id arxiv_https___arxiv_org_abs_2507_01743
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Position and Velocity Estimation Accuracy in MIMO-OFDM ISAC Networks: A Fisher Information Analysis
Pucci, Lorenzo
Arcangeloni, Luca
Giorgetti, Andrea
Signal Processing
This paper presents a theoretical framework to derive information-theoretic bounds on the estimation accuracy of target position and velocity in orthogonal frequency division multiplexing (OFDM)-based integrated sensing and communication (ISAC) networks composed of multiple cooperative and distributed multiple-input multiple-output (MIMO) base stations (BSs). Leveraging Fisher information analysis, we derive closed-form expressions for the Cramér-Rao lower bounds (CRLBs) in both monostatic and bistatic configurations. The framework is then extended to cooperative settings, including networks with multiple coordinated monostatic sensors and multistatic configurations, enabling joint estimation of target position and velocity. We systematically examine how estimation accuracy depends on key system parameters such as the number of BSs, bandwidth, antenna configuration, and network geometry. Numerical results highlight the performance gains enabled by cooperative sensing and provide insights to guide the design of future ISAC systems.
title Position and Velocity Estimation Accuracy in MIMO-OFDM ISAC Networks: A Fisher Information Analysis
topic Signal Processing
url https://arxiv.org/abs/2507.01743