On the Interference Alignment Designs for Secure Multiuser MIMO Systems

TL;DR

This paper introduces two interference alignment-based methods to enhance security in multiuser MIMO systems by minimizing information leakage to eavesdroppers and interference, with proven convergence and superior secrecy performance.

Contribution

The paper presents two novel IA schemes specifically designed for secure multiuser MIMO systems, optimizing precoding and receive matrices to improve secrecy rates.

Findings

Both IA schemes outperform conventional IA in secrecy sum rate.

The proposed methods effectively align wiretapped signals into subspaces or nullify them.

Feasible conditions and convergence proofs are provided for the algorithms.

Abstract

In this paper, we propose two secure multiuser multiple-input multiple-output transmission approaches based on interference alignment (IA) in the presence of an eavesdropper. To deal with the information leakage to the eavesdropper as well as the interference signals from undesired transmitters (Txs) at desired receivers (Rxs), our approaches aim to design the transmit precoding and receive subspace matrices to minimize both the total inter-main-link interference and the wiretapped signals (WSs). The first proposed IA scheme focuses on aligning the WSs into proper subspaces while the second one imposes a new structure on the precoding matrices to force the WSs to zero. When the channel state information is perfectly known at all Txs, in each proposed IA scheme, the precoding matrices at Txs and the receive subspaces at Rxs or the eavesdropper are alternatively selected to minimize the cost function of an convex optimization problem for every iteration. We provide the feasible conditions and the proofs of convergence for both IA approaches. The simulation results indicate that our two IA approaches outperform the conventional IA algorithm in terms of average secrecy sum rate.