Channel State Information-Free Artificial Noise-Aided Location-Privacy Enhancement

TL;DR

This paper introduces a novel artificial noise strategy that enhances location privacy by degrading illegitimate device localization without needing channel state information, showing significant accuracy reduction.

Contribution

A new framework for location-privacy preservation using structured artificial noise without channel state information at the transmitter is proposed.

Findings

Achieves 9dB degradation in illegitimate localization accuracy.

Structured artificial noise outperforms unstructured Gaussian noise.

Effective localization for legitimate devices is maintained.

Abstract

In this paper, an artificial noise-aided strategy is presented for location-privacy preservation. A novel framework for the reduction of location-privacy leakage is introduced, where structured artificial noise is designed to degrade the structure of the illegitimate devices' channel, without the aid of channel state information at the transmitter. Then, based on the location-privacy enhancement framework, a transmit beamformer is proposed to efficiently inject the structured artificial noise. Furthermore, the securely shared information is characterized to enable the legitimate devices to localize accurately. Numerical results show a 9dB degradation of illegitimate devices' localization accuracy is achieved, and validate the efficacy of structured artificial noise versus unstructured Gaussian noise.