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Globecom

On Feasibility of Interference Alignment for Secure Transmission in Cooperative MIMO Systems

Lin Hu, Jiabing Fan, Hong Wen, Qianbin Chen

Published Dec 8, 2024• 0 citations
Publisher

Abstract

To mitigate multi-user interference at legitimate receivers and assist secure transmission, artificial noise (AN) aided interference alignment (IA) is explored. The feasibility of traditional leakage minimization (LM) based IA is analyzed, including IA equations and rank constraint related to the secret signal transmission. We show that there exist two drawbacks which are not discussed in LM based IA security approaches: 1) the necessary condition for the feasibility of IA equations is loose, and 2) the secret signal cancellation may occur which makes secure transmission infeasible and in fact, there is no systematic analysis of this problem. We analyze the cause and establish a condition under which the secret signal cancellation is inevitable. Then a modified IA approach is proposed by implementing the max-eigenmode beamforming (MEB) for secure transmission. Compared with the traditional LM based IA, a tighter necessary condition can be established, and the secure transmission can be proctected. Numerical results confirm the effectiveness and usefulness of the modified IA approach.

DOI
10.1109/globecom52923.2024.10901765

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To mitigate multi-user interference at legitimate receivers and assist secure transmission, artificial noise (AN) aided interference alignment (IA) is explored. The feasibility of traditional leakage minimization (LM) based IA is analyzed, including IA equations and rank constraint related to the secret signal transmission. We show that there exist two drawbacks which are not discussed in LM based IA security approaches: 1) the necessary condition for the feasibility of IA equations is loose, and 2) the secret signal cancellation may occur which makes secure transmission infeasible and in fact, there is no systematic analysis of this problem. We analyze the cause and establish a condition under which the secret signal cancellation is inevitable. Then a modified IA approach is proposed by implementing the max-eigenmode beamforming (MEB) for secure transmission. Compared with the traditional LM based IA, a tighter necessary condition can be established, and the secure transmission can be proctected. Numerical results confirm the effectiveness and usefulness of the modified IA approach.
To enhance physical layer security (PLS) and mitigate interference at legitimate receivers, artificial noise (AN) assisted interference alignment (IA) is explored in cooperative multiple-input multiple-output (MIMO) systems. The feasibility of traditional leakage minimization (LM) based IA is analyzed. We show that there exist two drawbacks which are not discussed in traditional LM based IA: 1) the necessary condition for the feasibility of IA is loose, and 2) the secret signal cancellation may occur at the desired receiver, which makes secure transmission infeasible. We analyze the reason and establish a condition under which either the secret signal cancellation is inevitable or IA is infeasible. Then a modified IA is proposed. Compared with the traditional LM based IA, a tighter necessary condition is established and the secret signal is protected against cancellation. Moreover, we prove that the proposed condition guarantees the properness of system, which is a rigorous characterization of necessary conditions for achieving IA. Under assumption that the modified IA is feasible, we provide a secrecy enhancing design to maximize the secrecy rate. subject to a secrecy outage constraint. We also establish a condition under which a positive secrecy rate is feasible. Numerical results validate the effectiveness of the proposed approach.
Secure transfer of wireless information is becoming a critical issue in multi-user interference networks. In this paper, we consider secure transmission from a source (Alice) to a legitimate destination (Bob), coexisting with a passive eaves-dropper (Eve) andKKKtransceiver pairs. By assuming that only statistical channel state information (CSI) of Eve and local CSIs of legitimate users are known, a secrecy beamforming scheme with artificial noise (AN) is designed for secure transmission, and a modified interference alignment (IA) scheme is proposed for secrecy enhancement. Unlike the conventional AN-aided IA approaches which may lead to private signal cancellation, we propose a novel design modification with security protection. Moreover, a definite connection between improperness and in-feasibility of IA is established, to provide guiding insights on IA requirements. Based on a strict mathematical analysis, we further characterize the impact of transmit power on transceiver design and secrecy performance. Numerical results confirm that our design enables high transmission security with performance guarantee, and thus is suitable and stable for physical layer security (PLS) in multi-user interference networks.
This paper investigates physical layer security (PLS) in wireless interference networks. Specifically, we consider confidential transmission from a legitimate transmitter (Alice) to a legitimate receiver (Bob), in the presence of non-colluding passive eavesdroppers (Eves), as well as multiple legitimate transceivers. To mitigate interference at legitimate receivers and enhance PLS, artificial noise (AN) aided interference alignment (IA) is explored. However, the conventional leakage minimization (LM) based IA may exhibit confidential signal cancellation phenomenon. We theoretically analyze the cause and then establish a condition under which this phenomenon will occur almost surely. Moreover, we propose a means of avoiding this phenomenon by integrating the max-eigenmode beamforming (MEB) into the traditional LM based IA. By assuming that only statistical channel state informations (CSIs) of Eves and local CSIs of legitimate users are available, we derive a closed form expression for the secrecy outage probability (SOP), and establish a condition under which positive secrecy rate is achievable. To enhance security performance, an SOP constrained secrecy rate maximization (SRM) problem is formulated and an efficient numerical method is developed for the optimal solution. Numerical results confirm the effectiveness and the usefulness of the proposed approach.
We investigate the physical layer security (PLS) in multi-user interference networks. In particular, we consider secure transmission from a legitimate source (Alice) to a legitimate destination (Bob), coexisting with multiple passive eavesdroppers (Eves), as well as multiple legitimate transceivers. By assuming that only statistical channel state informations (CSIs) of Eves and local CSIs of legitimate users are available, we propose an artificial noise (AN) assisted interference alignment (IA) for security enhancement. Unlike traditional IA based security approaches which may result in secret signal cancellation, we design a modified alternating minimization (AM) scheme to overcome this threat, by incorporating the max-eigenmode beamforming (MEB) for secure transmission. Moreover, by partitioning the IA equation into three independent subsets and their combinations, a much tighter necessary condition for IA feasibility is established. We also provide guiding insights into the practical system designs, including useful guidelines for the selection of the dimension of AN. Furthermore, the power allocation ratio between the secret signal and the AN signal is optimized to minimize the secrecy outage probability (SOP), subject to a minimum secrecy rate constraint. Numerical results demonstrate that our design can enhance both quality and security of the secret signal, and thus is suitable and reliable for PLS in interference networks.
This paper investigates physical layer security (PLS) in wireless interference networks. Specifically, we consider confidential transmission from a legitimate transmitter (Alice) to a legitimate receiver (Bob), in the presence of non-colluding passive eavesdroppers (Eves), as well as multiple legitimate transceivers. To mitigate interference at legitimate receivers and enhance PLS, artificial noise (AN) aided interference alignment (IA) is explored. However, the conventional leakage minimization (LM) based IA may exhibit confidential signal cancellation phenomenon. We theoretically analyze the cause and then establish a condition under which this phenomenon will occur almost surely. Moreover, we propose a means of avoiding this phenomenon by integrating the max-eigenmode beamforming (MEB) into the traditional LM based IA. By assuming that only statistical channel state informations (CSIs) of Eves and local CSIs of legitimate users are available, we derive a closed form expression for the secrecy outage probability (SOP), and establish a condition under which positive secrecy rate is achievable. To enhance security performance, an SOP constrained secrecy rate maximization (SRM) problem is formulated and an efficient numerical method is developed for the optimal solution. Numerical results demonstrate the effectiveness and the usefulness of the proposed approach.
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-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. 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.