[Paper Review] Data-Aided Secure Massive MIMO Transmission with Active Eavesdropping

Yongpeng Wu, Chao-Kai Wen+4 more|arXiv (Cornell University)|Jan 22, 2018

Wireless Communication Security Techniques14 references3 citations

TL;DR

This paper proposes a data-aided secure massive MIMO transmission scheme for TDD multi-cell systems under active eavesdropping, where the eavesdropper jams both uplink pilot and data phases. By exploiting uplink pilots and data for channel estimation, the scheme leverages the asymptotic eigenspace separation between desired users and eavesdroppers due to power differences, enabling effective precoding that achieves significant secrecy rate gains under strong active attacks, even when the eavesdropper's signal power exceeds that of the legitimate user.

ABSTRACT

In this paper, we study the design of secure communication for time division duplexing multi-cell multi-user massive multiple-input multiple-output (MIMO) systems with active eavesdropping. We assume that the eavesdropper actively attacks the uplink pilot transmission and the uplink data transmission before eavesdropping the downlink data transmission phase of the desired users. We exploit both the received pilots and data signals for uplink channel estimation. We show analytically that when the number of transmit antennas and the length of the data vector both tend to infinity, the signals of the desired user and the eavesdropper lie in different eigenspaces of the received signal matrix at the base station if their signal powers are different. This finding reveals that decreasing (instead of increasing) the desire user's signal power might be an effective approach to combat a strong active attack from an eavesdropper. Inspired by this result, we propose a data-aided secure downlink transmission scheme and derive an asymptotic achievable secrecy sum-rate expression for the proposed design. Numerical results indicate that under strong active attacks, the proposed design achieves significant secrecy rate gains compared to the conventional design employing matched filter precoding and artificial noise generation.

Motivation & Objective

• To address the critical security threat posed by active eavesdroppers in TDD massive MIMO systems who jam uplink training and data phases.
• To overcome the limitations of conventional physical layer security designs that fail under strong pilot contamination attacks.
• To develop a secure downlink transmission scheme that leverages uplink data and pilots for improved channel estimation and secrecy rate performance.
• To theoretically analyze and demonstrate that signal power differences lead to eigenspace separation between legitimate users and eavesdroppers in the large-antenna regime.
• To derive an asymptotic achievable secrecy sum-rate expression for the proposed data-aided secure transmission scheme.

Proposed method

• The base station uses both uplink pilots and uplink data signals to estimate the channel, improving robustness against eavesdropper jamming.
• The scheme exploits the fact that, as the number of transmit antennas and data symbols grow large, the desired user and eavesdropper signals lie in different eigenspaces of the uplink received signal matrix due to differing signal powers.
• A data-aided channel estimation method is developed to enhance accuracy despite active eavesdropping, enabling better precoder design.
• The secrecy sum-rate is analyzed asymptotically, deriving a closed-form expression that accounts for the impact of eavesdropper interference and channel estimation errors.
• Precoding is designed based on the estimated channels to maximize secrecy rate, with performance evaluated under strong active attacks.

Experimental results

Research questions

• RQ1 Can eigenspace separation between legitimate users and eavesdroppers be achieved in massive MIMO systems when the eavesdropper actively jams uplink training and data transmission?
• RQ2 Does leveraging uplink data for channel estimation improve secrecy performance in the presence of strong active eavesdropping?
• RQ3 What is the asymptotic behavior of the secrecy sum-rate when the number of transmit antennas and data symbols both tend to infinity under active eavesdropping?
• RQ4 Can decreasing the legitimate user’s signal power improve security in the presence of a strong eavesdropper, contrary to conventional intuition?
• RQ5 How does the proposed data-aided scheme compare to conventional matched filter precoding and artificial noise schemes under strong active attacks?

Key findings

• When the number of transmit antennas and data symbols both tend to infinity, the signals of the desired user and the eavesdropper lie in different eigenspaces of the uplink received signal matrix, due to their differing signal powers.
• The proposed scheme achieves significant secrecy rate gains over conventional designs—especially under strong active attacks—by exploiting this eigenspace separation.
• The asymptotic achievable secrecy sum-rate expression is derived, showing that the eavesdropper’s effective channel gain vanishes as the number of antennas increases.
• The analysis reveals that increasing the power gap between the legitimate user and the eavesdropper enhances separation, making it beneficial to reduce the legitimate user’s signal power in some cases.
• Numerical results confirm that the proposed data-aided scheme outperforms conventional matched filter precoding and artificial noise schemes in terms of secrecy rate under strong active eavesdropping.