Secure communications using interference alignment in MIMO interference channels

2015 International Conference on Communications, Management and Telecommunications (ComManTel)

2015

In this paper, we formulate the interference alignment (IA) problem for a multiuser multiple-input multiple-output (MIMO) system in the presence of an eavesdropper as a rank constrained rank minimization (RCRM) problem. The aim of the proposed rank minimization IA schemes is to find the precoding and receiver subspace matrices to align interference and wiretapped signals into the lowest dimension subspaces while keeping the desired signal subspace spanning full available spatial dimensions. To deal with the nonconvexity of the rank function, we present two convex relaxations of the RCRM problem, namely nuclear norm (NN) and reweighted nuclear norm (RNN), and transform the rank constraints to equivalent and tractable ones. We then derive a coordinate decent approach to obtain the solutions for IA schemes. The simulation results show that our proposed IA designs outperform the conventional IA design in terms of average secrecy sum rate. On the other hand, our proposed designs perform the same or better than other secure IA schemes which account for low interference and wiretapped signal power rather than for low dimensions of interference and wiretapped signal matrices in the systems which achieve the perfect IA.

Section: System Model and Problem Formulationmentioning

confidence: 99%

Interference alignment designs for secure multiuser MIMO systems: rank constrained rank minimization approach

2015 International Conference on Communications, Management and Telecommunications (ComManTel)

2015

“…Conditions (6) guarantees that the intended signal at the k-th Rx achieves d degree of freedom when H H H k,k is full rank. The condition (7) ensures no inter-main link interference (IMLI), i.e., no interference among the legitimate users, at the k-th Rx. Condition (8) makes certain that there is no leakage signal wiretapped at the eavesdropper or the (K + 1)-th Rx.…”

Section: Wslm For Secrecy Multiuser Mimo Communication Via Iamentioning

confidence: 99%

Wiretapped signal leakage minimization for secure multiuser MIMO systems via interference alignment

2015 International Conference on Advanced Technologies for Communications (ATC)

et al. 2015

Abstract-In this paper, interference alignment (IA) is designed for secure multiuser multiple-input multiple-output systems in the presence of an eavesdropper. The proposed IA technique designs the transmit precoding and receiving subspace matrices to minimize both the total inter-main-link interference and the wiretapped signals. With perfect channel state information is known at the transmitters (Txs), the cost function of the optimization problem is alternatively minimized over the precoding matrices at the Txs and the receiving subspace matrices at the receivers (Rxs) and the eavesdropper. The feasible condition, the proof of convergence of the proposed IA approach are provided. Numerical results reveal a significant improvement in terms of average secrecy sum rate of our IA algorithm as compared to the conventional IA design.

“…Reference [28] demonstrated that the secure transmission is also possible when the number of antennas at the legitimate Tx and Rx is greater than that of the eavesdropper. However, a detailed IA design for secure multisuer MIMO communication networks has not been explored in [28]. Alternatively, the authors in [29], [30] have exploited cooperative jamming schemes with IA for secrecy communications.…”

Section: Introductionmentioning

confidence: 99%

On the Interference Alignment Designs for Secure Multiuser MIMO Systems

IEICE Trans. Fundamentals

et al. 2017

Abstract-In this paper, we propose two secure multiuser multiple-input multiple-output (MIMO) 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-mainlink 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. In each proposed IA scheme, the precoding matrices and the receive subspaces at the legitimate users are alternatively selected to minimize the cost function of a 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 the average secrecy sum rate.