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Protecting Human Activity Signatures in Compressed IEEE 802.11 CSI Feedback

Mohamed Seif, Atsutse Kludze, Yasaman Ghasempour, H. Vincent Poor, Doru Calin, Andrea J. Goldsmith

TL;DR

The paper tackles privacy leakage from explicit CSI feedback in IEEE 802.11 by introducing a standards-compatible differential privacy mechanism that privatizes the Givens rotation and phase angles used for compressed beamforming. It replaces deterministic angle quantization with an $\\\psilon$-DP stochastic quantizer (DP-SQ), deriving sensitivity bounds and a subspace-distortion guarantee to quantify the tradeoff between privacy and beamforming utility. Through numerical simulations, the authors demonstrate strong privacy protection—disrupting adversaries' activity and speed inference—while incurring only modest, controllable degradation to downlink performance, especially at higher angular resolutions. The approach preserves the existing 802.11 feedback format, suggesting practical applicability and potential extension to future wireless standards and systems.

Abstract

Explicit channel state information (CSI) feedback in IEEE~802.11 conveys \emph{transmit beamforming directions} by reporting quantized Givens rotation and phase angles that parametrize the right-singular subspace of the channel matrix. Because these angles encode fine-grained spatial signatures of the propagation environment, recent work have shown that plaintext CSI feedback can inadvertently reveal user activity, identity, and location to passive eavesdroppers. In this work, we introduce a standards-compatible \emph{differentially private (DP) quantization mechanism} that replaces deterministic angular quantization with an $\varepsilon$-DP stochastic quantizer applied directly to the Givens parameters of the transmit beamforming matrix. The mechanism preserves the 802.11 feedback structure, admits closed-form sensitivity bounds for the angular representation, and enables principled privacy calibration. Numerical simulations demonstrate strong privacy guarantees with minimal degradation in beamforming performance.

Protecting Human Activity Signatures in Compressed IEEE 802.11 CSI Feedback

TL;DR

The paper tackles privacy leakage from explicit CSI feedback in IEEE 802.11 by introducing a standards-compatible differential privacy mechanism that privatizes the Givens rotation and phase angles used for compressed beamforming. It replaces deterministic angle quantization with an -DP stochastic quantizer (DP-SQ), deriving sensitivity bounds and a subspace-distortion guarantee to quantify the tradeoff between privacy and beamforming utility. Through numerical simulations, the authors demonstrate strong privacy protection—disrupting adversaries' activity and speed inference—while incurring only modest, controllable degradation to downlink performance, especially at higher angular resolutions. The approach preserves the existing 802.11 feedback format, suggesting practical applicability and potential extension to future wireless standards and systems.

Abstract

Explicit channel state information (CSI) feedback in IEEE~802.11 conveys \emph{transmit beamforming directions} by reporting quantized Givens rotation and phase angles that parametrize the right-singular subspace of the channel matrix. Because these angles encode fine-grained spatial signatures of the propagation environment, recent work have shown that plaintext CSI feedback can inadvertently reveal user activity, identity, and location to passive eavesdroppers. In this work, we introduce a standards-compatible \emph{differentially private (DP) quantization mechanism} that replaces deterministic angular quantization with an -DP stochastic quantizer applied directly to the Givens parameters of the transmit beamforming matrix. The mechanism preserves the 802.11 feedback structure, admits closed-form sensitivity bounds for the angular representation, and enables principled privacy calibration. Numerical simulations demonstrate strong privacy guarantees with minimal degradation in beamforming performance.

Paper Structure

This paper contains 12 sections, 2 theorems, 44 equations, 9 figures, 1 table.

Table of Contents

  1. Introduction
  2. Privacy Concerns in Explicit Beamforming
  3. System Model
  4. Communication Model
  5. Compressed CSI Feedback via Givens Angles
  6. Privacy Threat Model
  7. Stochastic Quantization for Privacy-Preserving Beamforming
  8. Stochastic Quantization
  9. Differential Privacy
  10. DP Stochastic Quantization (DP--SQ) Mechanism
  11. Numerical Simulations
  12. Conclusion & Future Work

Key Result

Lemma 1

Let each quantizer have step size $\Delta_\phi = \tfrac{2\pi}{2^{B_\phi}}$ and $\Delta_\psi = \tfrac{\pi/2}{2^{B_\psi}}$. Now, define the term $\kappa(\varepsilon) \triangleq \frac{e^{\varepsilon}-1}{e^{\varepsilon}+1}$. The proposed privacy mechanism yields the following MSE:

Figures (9)

  • Figure 1: An adversarial wireless setting where: $(1)$ a passive eavesdropper leverages the physical-layer structure of received Wi-Fi signals—e.g., through spectrogram measurements or the rotation-angle parameters conveyed during CSI feedback, and $(2)$ infer sensitive user or environmental information without authorization.
  • Figure 2: Closed-loop CSI feedback architecture with $N_t$ transmit antennas, $N_r$ receive antennas, $N_s$ spatial streams, a shared angles codebook, and the proposed DP--SQ feedback quantization.
  • Figure 3: An example for CSI amplitude spectrogram illustrating activity-dependent channel dynamics for a user moving within an indoor environment. Distinct Doppler patterns correspond to transitions between standing/slow motion, walking, jogging, and running, reflecting how user activity modulates the wireless channel over time.
  • Figure 4: Information leakage from the compressed CSI packets. The adversary is assumed to have a lower SNR then the legitimate AP ($20$ dB vs $5$ dB) but is still able to accurately reconstruct the full CSI and estimate the STA's speed from the compressed feedback packets.
  • Figure 5: Impact of privacy-preserving angle feedback on BER for different modulation orders and angle quantization resolutions where $\varepsilon = 0.1$.
  • ...and 4 more figures

Theorems & Definitions (3)

  • Definition 1: ($\varepsilon,\delta$)-DP dwork2014algorithmic
  • Lemma 1
  • Theorem 1: Expected Subspace Distortion under DP--SQ