Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Log inSign up
Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Blog
Job Board
Q3AS

© 2026 Aqora Quantum S.A.S.

TermsPrivacyLegal Notice

Confidential Transmission Based on Statistical CSI Using DFT Beamforming

Hua Fu, Yanfeng Sun, Xiaoyu Zhang

Published Jul 8, 2023• 0 citations
Publisher

Abstract

Statistical channel state information (CSI) can be obtained by pre-measuring the user’s channel, unlike instantaneous CSI which is only available after the user has accessed the network. Hence, the statistical CSI can be used to achieve confidential transmission and protect the access process of legitimate users. In this paper, we propose a beam selection scheme based on statistical CSI for discrete Fourier transform beamforming. Assuming that the statistical CSIs of the legitimate user and the eavesdropper are available at the base station, we adopt artificial noise (AN) in transmission and minimize the signal-to-noise-plus-interference ratio of the eavesdropper. The beam selection scheme can be converted into a semidefinite program problem. The performance of the system has been tested in both line-of-sight and non-line-of-sight scenarios using a 5G clustered delay line channel model. The simulation results show that, by transmitting AN, the performance of eavesdropper rapidly degrades when the eavesdropper moves away from the legitimate user.

DOI
10.1109/icsip57908.2023.10271085

Related papers

Artificial Noise assisted Secure Transmission using Novel Beamforming Scheme based on Statistical CSI

Xiaoyu Zhang, Yutao Lu, Hua Fu +1 more

We propose a secure transmission scheme that employs artificial noise (AN) to enhance information security. This scheme uses a novel beam design method based on a specific type of statistical Channel State Information (CSI) known as the channel statistical covariance matrix. The base station can acquire this matrix through prior measurements. By performing eigenvalue decomposition on this matrix, we can extract valuable engineering insights from its eigenvalue and eigenvectors, which represent beam domain information within the channel. Leveraging this information, we further design an optimization problem to minimize the eavesdropper's Signal-to-Noise-Plus-Interference Ratio (SINR) through joint optimization of beam selection and power allocation. Eventually, an iterative algorithm is proposed to solve this optimization problem. Numerical results reveal favorable secrecy performance of our beamforming scheme under CDL channel models.

IEEE International Conference on Communication Technology (ICCT)•Oct 20, 2023•1 citation

MISO secrecy transmission via designing artificial noise by receiver under perfect and imperfect CSI

Guyue Li, Aiqun Hu

This paper proposes a physical-layer secrecy transmission based on artificial noise (AN) for a multi-input single-output (MISO) channel overheard by one single-antenna eavesdropper. Legitimate receiver transmits AN using beamforming to improve the secret capacity. The AN is designed for two cases assuming that legitimate receiver has perfect or imperfect knowledge of eavesdropper's channel state information (CSI). The optimization problem of AN design in both cases are not convex. A one-dimensional line search on a sequence of semidefinite programs (SDP) is proposed to solve the problem in perfect CSI case through reformulation. In the case with imperfect CSI, the beamforming and AN vectors are designed for achieving quality of service discrimination. The problem is approximated to be a convex SDP problem by relaxing some restrictions. Furthermore, the optimal covariance is shown to be of rank one. Simulation results verify that our methods precede the existed AN aided scheme.

IEEE International Conference on Computer and Communications (ICCC)•Oct 1, 2016•2 citations

Robust Beamforming for Security in MIMO Wiretap Channels With Imperfect CSI

Amitav Mukherjee, Arnold Lee Swindlehurst

In this paper, we investigate methods for reducing the likelihood that a message transmitted between two multi-antenna nodes is intercepted by an undetected eavesdropper. In particular, we focus on the judicious transmission of artificial interference to mask the desired signal at the time it is broadcast. Unlike previous work that assumes some prior knowledge of the eavesdropper's channel and focuses on maximizing secrecy capacity, we consider the case where no information regarding the eavesdropper is available, and we use signal-to-interference-plus-noise-ratio (SINR) as our performance metric. Specifically, we focus on the problem of maximizing the amount of power available to broadcast a jamming signal intended to hide the desired signal from a potential eavesdropper, while maintaining a prespecified SINR at the desired receiver. The jamming signal is designed to be orthogonal to the information signal when it reaches the desired receiver, assuming both the receiver and the eavesdropper employ optimal beamformers and possess exact channel state information (CSI). In practice, the assumption of perfect CSI at the transmitter is often difficult to justify. Therefore, we also study the resulting performance degradation due to the presence of imperfect CSI, and we present robust beamforming schemes that recover a large fraction of the performance in the perfect CSI case. Numerical simulations verify our analytical performance predictions, and illustrate the benefit of the robust beamforming schemes.

arXiv:1009.2274•IEEE Transactions on Signal Processing•Sep 22, 2010•454 citations

Artificial Noise Assisted Secure Massive MIMO Transmission Exploiting Statistical CSI

Wenjin Wang, Chen Xu, Li You +2 more

For the single-cell massive multiple-input multiple-output (MIMO) downlink transmission, we investigate an artificial noise (AN) assisted secure transmission strategy where the base station has only access to statistical channel state information (CSI) of the legitimate user terminals and the eavesdropper. By maximizing a lower bound of the ergodic secrecy sum rate, we figure out the eigenvectors of the optimal secrecy signal and AN transmit covariance matrices in the closed-form. Notably, such a solution reveals that it is more favorable to transmit both the secrecy signals and the AN in the beam domain, by which we translate the original problem into a simpler power allocation problem in the beam domain. Building on the approaches of sequential optimization and the deterministic equivalent, we further propose an iterative algorithm for power allocation with guaranteed convergence to a local optimum. Numerical results show the superior performance of the proposed approach compared with the traditional one without AN.

IEEE Communications Letters•Oct 15, 2019•27 citations

Joint Feedback and Artificial Noise Design for Secure Communications Over Fading Channels Without Eavesdropper's CSI

Hongliang He, Pinyi Ren, Qinghe Du +1 more

Secure communication with noisy feedback is studied in this correspondence. Unlike the majority of previous research efforts where the eavesdropper's channel state information (CSI)-either instantaneous or statistical CSI, is known by the legitimate users, a joint feedback and artificial noise scheme without any eavesdropper's CSI is proposed. The proposed scheme lets the source and the legitimate destination alternatively transmit private messages and degrade the eavesdropper's channel quality in all transmission phases. An insightful discovery is that if the transmit power is lager than a certain threshold, a positive secrecy capacity can be achieved, which overcomes the problem that the secrecy cannot be achieved when the legitimate user's CSI is worse than the eavesdropper's. The secrecy capacity maximization problem is investigated by adaptive power allocation for the private signals and the artificial noise where a near optimal solution of the power of artificial noise is obtained under the high SNR situation. Finally, the numerical results verify the theoretical analysis and illustrate the secrecy performance of the proposed scheme.

IEEE Transactions on Vehicular Technology•Jul 20, 2017•21 citations

Robust Secure Beamforming for Multiuser MISO Wiretap Channels

Yuchong Li, Lijian Zhang, Yuguo Wu +1 more

Physical layer security has recently emerged as a promising approach to provide secure wireless communications. Physical layer security technology is the key means to achieve security and communication integration. The built-in security mechanism based on the characteristics of wireless channel provides a feasible idea for the realization of “one secret at a time”. It has important application prospects in integrity protection of service data, Internet of things (IoT) lightweight encryption and blockchain wireless security technology. In this paper, we consider the scenario of a unicast multiuser multiple-input single-output (MISO) downlink system in the presence of multiple single-antenna passive eavesdroppers. Instead of assuming perfect channel state information (CSI), we investigate the artificial noise (AN)-aided robust transmit beamforming scheme with imperfect CSI on legitimate receivers and no CSI regarding eavesdroppers at the transmitter. Under the fixed total transmit power, the information symbol and the AN are transmitted concurrently. We aim to guarantee each legitimate receiver's signal-to-interference-and-noise ratio(SINR) outage probability below a preset level with minimum power. Hence, as much power as possible can be allocated to AN to confuse the eavesdroppers. In order to reduce the negative impact on the legitimate receivers, the AN is transmitted in the null space of the estimated legitimate channels. To deal with this nonconvex optimization problem, a rank relaxed formulation is obtained by employing semidefinite relaxation (SDR). Then we propose two approaches by using Bernstein-type inequality and S-procedure, respectively, to transform the probabilistic constraints into deterministic constraints. The optimization problem is reformulated as a convex semidefinite program (SDP). Simulation results show that the proposed approaches have better performances than the non-robust approach.

International Conference on Smart BlockChain (SmartBlock)•Oct 1, 2020•3 citations
Statistical channel state information (CSI) can be obtained by pre-measuring the user’s channel, unlike instantaneous CSI which is only available after the user has accessed the network. Hence, the statistical CSI can be used to achieve confidential transmission and protect the access process of legitimate users. In this paper, we propose a beam selection scheme based on statistical CSI for discrete Fourier transform beamforming. Assuming that the statistical CSIs of the legitimate user and the eavesdropper are available at the base station, we adopt artificial noise (AN) in transmission and minimize the signal-to-noise-plus-interference ratio of the eavesdropper. The beam selection scheme can be converted into a semidefinite program problem. The performance of the system has been tested in both line-of-sight and non-line-of-sight scenarios using a 5G clustered delay line channel model. The simulation results show that, by transmitting AN, the performance of eavesdropper rapidly degrades when the eavesdropper moves away from the legitimate user.
We propose a secure transmission scheme that employs artificial noise (AN) to enhance information security. This scheme uses a novel beam design method based on a specific type of statistical Channel State Information (CSI) known as the channel statistical covariance matrix. The base station can acquire this matrix through prior measurements. By performing eigenvalue decomposition on this matrix, we can extract valuable engineering insights from its eigenvalue and eigenvectors, which represent beam domain information within the channel. Leveraging this information, we further design an optimization problem to minimize the eavesdropper's Signal-to-Noise-Plus-Interference Ratio (SINR) through joint optimization of beam selection and power allocation. Eventually, an iterative algorithm is proposed to solve this optimization problem. Numerical results reveal favorable secrecy performance of our beamforming scheme under CDL channel models.
This paper proposes a physical-layer secrecy transmission based on artificial noise (AN) for a multi-input single-output (MISO) channel overheard by one single-antenna eavesdropper. Legitimate receiver transmits AN using beamforming to improve the secret capacity. The AN is designed for two cases assuming that legitimate receiver has perfect or imperfect knowledge of eavesdropper's channel state information (CSI). The optimization problem of AN design in both cases are not convex. A one-dimensional line search on a sequence of semidefinite programs (SDP) is proposed to solve the problem in perfect CSI case through reformulation. In the case with imperfect CSI, the beamforming and AN vectors are designed for achieving quality of service discrimination. The problem is approximated to be a convex SDP problem by relaxing some restrictions. Furthermore, the optimal covariance is shown to be of rank one. Simulation results verify that our methods precede the existed AN aided scheme.
In this paper, we investigate methods for reducing the likelihood that a message transmitted between two multi-antenna nodes is intercepted by an undetected eavesdropper. In particular, we focus on the judicious transmission of artificial interference to mask the desired signal at the time it is broadcast. Unlike previous work that assumes some prior knowledge of the eavesdropper's channel and focuses on maximizing secrecy capacity, we consider the case where no information regarding the eavesdropper is available, and we use signal-to-interference-plus-noise-ratio (SINR) as our performance metric. Specifically, we focus on the problem of maximizing the amount of power available to broadcast a jamming signal intended to hide the desired signal from a potential eavesdropper, while maintaining a prespecified SINR at the desired receiver. The jamming signal is designed to be orthogonal to the information signal when it reaches the desired receiver, assuming both the receiver and the eavesdropper employ optimal beamformers and possess exact channel state information (CSI). In practice, the assumption of perfect CSI at the transmitter is often difficult to justify. Therefore, we also study the resulting performance degradation due to the presence of imperfect CSI, and we present robust beamforming schemes that recover a large fraction of the performance in the perfect CSI case. Numerical simulations verify our analytical performance predictions, and illustrate the benefit of the robust beamforming schemes.
For the single-cell massive multiple-input multiple-output (MIMO) downlink transmission, we investigate an artificial noise (AN) assisted secure transmission strategy where the base station has only access to statistical channel state information (CSI) of the legitimate user terminals and the eavesdropper. By maximizing a lower bound of the ergodic secrecy sum rate, we figure out the eigenvectors of the optimal secrecy signal and AN transmit covariance matrices in the closed-form. Notably, such a solution reveals that it is more favorable to transmit both the secrecy signals and the AN in the beam domain, by which we translate the original problem into a simpler power allocation problem in the beam domain. Building on the approaches of sequential optimization and the deterministic equivalent, we further propose an iterative algorithm for power allocation with guaranteed convergence to a local optimum. Numerical results show the superior performance of the proposed approach compared with the traditional one without AN.
Secure communication with noisy feedback is studied in this correspondence. Unlike the majority of previous research efforts where the eavesdropper's channel state information (CSI)-either instantaneous or statistical CSI, is known by the legitimate users, a joint feedback and artificial noise scheme without any eavesdropper's CSI is proposed. The proposed scheme lets the source and the legitimate destination alternatively transmit private messages and degrade the eavesdropper's channel quality in all transmission phases. An insightful discovery is that if the transmit power is lager than a certain threshold, a positive secrecy capacity can be achieved, which overcomes the problem that the secrecy cannot be achieved when the legitimate user's CSI is worse than the eavesdropper's. The secrecy capacity maximization problem is investigated by adaptive power allocation for the private signals and the artificial noise where a near optimal solution of the power of artificial noise is obtained under the high SNR situation. Finally, the numerical results verify the theoretical analysis and illustrate the secrecy performance of the proposed scheme.
Physical layer security has recently emerged as a promising approach to provide secure wireless communications. Physical layer security technology is the key means to achieve security and communication integration. The built-in security mechanism based on the characteristics of wireless channel provides a feasible idea for the realization of “one secret at a time”. It has important application prospects in integrity protection of service data, Internet of things (IoT) lightweight encryption and blockchain wireless security technology. In this paper, we consider the scenario of a unicast multiuser multiple-input single-output (MISO) downlink system in the presence of multiple single-antenna passive eavesdroppers. Instead of assuming perfect channel state information (CSI), we investigate the artificial noise (AN)-aided robust transmit beamforming scheme with imperfect CSI on legitimate receivers and no CSI regarding eavesdroppers at the transmitter. Under the fixed total transmit power, the information symbol and the AN are transmitted concurrently. We aim to guarantee each legitimate receiver's signal-to-interference-and-noise ratio(SINR) outage probability below a preset level with minimum power. Hence, as much power as possible can be allocated to AN to confuse the eavesdroppers. In order to reduce the negative impact on the legitimate receivers, the AN is transmitted in the null space of the estimated legitimate channels. To deal with this nonconvex optimization problem, a rank relaxed formulation is obtained by employing semidefinite relaxation (SDR). Then we propose two approaches by using Bernstein-type inequality and S-procedure, respectively, to transform the probabilistic constraints into deterministic constraints. The optimization problem is reformulated as a convex semidefinite program (SDP). Simulation results show that the proposed approaches have better performances than the non-robust approach.