Privacy Preservation in MIMO-OFDM Localization Systems: A Beamforming Approach

TL;DR

This paper proposes a beamforming optimization method for MIMO-OFDM systems that enhances legitimate user localization accuracy while safeguarding against unauthorized localization attempts, thereby preserving user privacy.

Contribution

It introduces a novel beamforming approach using penalty dual decomposition to optimize localization privacy in MIMO-OFDM systems, balancing accuracy and privacy constraints.

Findings

The proposed method improves legitimate localization accuracy.

It effectively limits unauthorized localization attempts.

Numerical results show superiority over existing benchmarks.

Abstract

We investigate an uplink MIMO-OFDM localization scenario where a legitimate base station (BS) aims to localize a user equipment (UE) using pilot signals transmitted by the UE, while an unauthorized BS attempts to localize the UE by eavesdropping on these pilots, posing a risk to the UE's location privacy. To enhance legitimate localization performance while protecting the UE's privacy, we formulate an optimization problem regarding the beamformers at the UE, aiming to minimize the Cram\'er-Rao bound (CRB) for legitimate localization while constraining the CRB for unauthorized localization above a threshold. A penalty dual decomposition optimization framework is employed to solve the problem, leading to a novel beamforming approach for location privacy preservation. Numerical results confirm the effectiveness of the proposed approach and demonstrate its superiority over existing benchmarks.