Artificial Noise Signals Research Articles

Fluid Antenna Enabling Secret Communications

Recent researches have revealed that fluid antenna, a new position-switchable antenna technology, can make use of the spatial moments of deep fades of the interference signal occurred naturally due to multipath for multiple access. In this letter, this phenomenon is exploited in a physical layer security setup where a base station (BS) transmits an information-bearing signal to a legitimate user and an artificial noise (AN) signal to a potential eavesdropper while the user is equipped with a fluid antenna to overcome the AN signal. The proposed approach needs no effort from the base station (BS) to avoid the AN signal from harming the legitimate user. Trying to enhance the secrecy rate, we study the power allocation of the information-bearing and AN signals if the channel state information (CSI) is available at the BS. Both perfect and imperfect CSI scenarios are investigated. Simulation results demonstrate that the proposed system, with a single fluid antenna with one radio-frequency (RF) chain at the user, achieves the secrecy rate that is achievable by the user utilizing maximal ratio combining (MRC) with many antennas instead, and is the only approach robust to CSI uncertainties of the eavesdropper, requiring no power allocation nor beamforming at the BS.

Sensing and Secure NOMA-Assisted mMTC Wireless Networks

Throughout this study, a novel network model for massive machine-type communications (mMTC) is proposed using a compressive sensing (CS) algorithm and a non-orthogonal multiple access (NOMA) scheme. Further, physical-layer security (PLS) is applied in this network to provide secure communication. We first assume that all the legitimate nodes operate in full-duplex mode; then, an artificial noise (AN) signal is emitted while receiving the signal from the head node to confuse eavesdroppers (Eve). A convex optimization tool is used to detect the active number of nodes in the proposed network using a sparsity-aware maximum a posteriori (S-MAP) detection algorithm. The sensing-aided secrecy sum rate of the proposed network is analyzed and compared with the sum rate of the network without sensing, and the closed-form expression of the secrecy outage probability of the proposed mMTC network is derived. Finally, our numerical results demonstrate the impact of an active sensing algorithm in the proposed mMTC network; improvement in the secrecy outage of the proposed network is achieved through increasing the distance of the Eve node.

Interference Alignment for Physical Layer Security in Multi-User Networks With Passive Eavesdroppers

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.

Resource Allocation for Joint Interference Management and Security Enhancement in Cellular-Connected Internet-of-Drones Networks

Internet-of-drones (IoD) systems require enhanced data transmission security and efficient interference management to accommodate the rapidly growing drone-based and rate-intensive applications. This paper develops a novel resource allocation scheme to jointly manage interference and enhance the physical layer security of cellular-connected IoD networks in the presence of a multi-band eavesdropping drone. Our envisioned cellular-connected IoD network has multiple full-duplex cellular base stations (CBSs), where each CBS reserves an orthogonal cellular radio resource block (RRB) for the aerial communication links. To efficiently utilize the cellular RRBs, each CBS is connected to a cluster of data transmitting drones using uplink non-orthogonal multiple access (NOMA) scheme. In addition, all the CBSs simultaneously transmit artificial noise signals to weaken the eavesdropper links. A joint optimization problem, considering the transmit power allocation and clustering of the legitimate drones, and the jamming power allocation of the CBSs, is formulated to maximize the worst-case average sum-secrecy-rate of the network. The joint optimization problem is decomposed into drone-clustering and power allocation sub-problems to obtain an efficient solution. A multi-agent reinforcement-learning framework is devised to solve the drone-clustering sub-problem. Meanwhile, the transmit and jamming power allocation sub-problem is solved by employing fractional programming, successive convex approximation, and alternating optimization techniques. By iteratively solving these two sub-problems, a convergent resource allocation algorithm, namely, <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\underline{\text{s}}$</tex-math></inline-formula> ecurity and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\underline{\text{i}}$</tex-math></inline-formula> nterference management with <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\underline{\text{re}}$</tex-math></inline-formula> inforcement-learning and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\underline{\text{N}}$</tex-math></inline-formula> OMA (SIREN), is proposed. The superiority of SIREN over several benchmark schemes is verified via extensive simulations.

Resource Allocation Optimization for Secure Multidevice Wirelessly Powered Backscatter Communication With Artificial Noise

Wirelessly powered backscatter communications (WPBC) is an emerging technology for providing continuous energy and ultra-low power communications. Despite some progress in WPBC systems, resource allocation for multiple devices towards secure backscatter communications (BC) and efficient-energy harvesting (EH) requests a deep-insight investigation. In this paper, we consider a WPBC system in which a full-duplex access point (AP) transmits multi-sinewave signals to power backscatter devices (BDs) and injects artificial noise (AN) to secure their backscatter transmissions. To maximize the minimum harvested energy and ensure fairness and security of all BDs, we formulate an optimization problem by jointly considering the backscatter time, power splitting ratio between multi-sinewave and AN, and signal power allocation. For a single-BD system, we characterize the achievable secrecy rate-energy region with a non-linear energy harvester and propose two algorithms to solve an energy maximization problem. We then analyze the effect of multi-sinewave and AN signals on BD’s secrecy rate and harvested energy through simulations and proof-of-concept experiments. For a multi-BD system, we propose an iterative algorithm by leveraging block successive upper-bound minimization (BSUM) techniques to solve the non-convex problem of fair resource allocation and show its convergence and complexity. Numerical results show the proposed algorithm achieves optimal and equitable harvested energy for all BDs with satisfying the security constraint.

Secure Transmission for MISO Wiretap Channels Using General Multi-Fractional Fourier Transform: An Approach in Signal Domain

In this paper, we propose a physical layer secure transmission technology based on multi-components for multiple-input single-output (MISO) systems. The scheme mainly realizes physical layer security (PLS) in General Multi-Fractional Fourier Transform (GMFRFT) signal domain, which is different from traditional schemes that rely on the spatial domain. Different GMFRFT components are transmitted by multiple antennas at the transmitter, then the legitimate receiver and the eavesdropper receive the superposition of multiple non-orthogonal components. The resulting mutual interference will reduce the signal-to-interference and noise (SINR) at the eavesdropper, but without affecting the legitimate receiver. Because the legitimate receiver receives the non-contaminated GMFRFT signal due to designing multi-components at the transmitter, while the eavesdropper receives the signal whose constraint relations in the GMFRFT signal domain are destroyed, which will cause the energy loss of the information bearing signal. Furthermore, in order to achieve the maximum secrecy capacity, the selection method of GMFRFT transform order is given to adjust the power allocation among GMFRFT components. Compared with the scheme based on artificial noise (AN), the advantages of our scheme are: 1) our scheme can further reduce the capacity of wiretap channel while not requiring the transmitter to use partial power to transmit meaningless artificial noise signals; 2) our scheme outperforms AN-based schemes when the available spatial degrees of freedom are limited. Simulation results are provided to demonstrate the secrecy performance of the proposed scheme.

AN-aided beamforming for IRS-assisted SWIPT systems

This paper studies artificial noise (AN)-aided beamforming design in an intelligent reflecting surface (IRS)-assisted system empowered by simultaneous wireless information and power transfer (SWIPT) technique. Multiple power splitting (PS) single-antenna receivers simultaneously receive information and energy from a multi-antenna base station (BS). Although all users are legitimate, in each transmission interval only one receiver is authorized to receive information and the others are only allowed to harvest power which are considered as unauthorized receivers (URs). To prevent information decoding by URs, AN signal is transmitted from the BS. We adopt a non-linear model for energy harvesting. In the optimization problem, we minimize the total transmit power, and for this purpose, we utilize an alternating optimization (AO) algorithm. For the non-convex rank-one constraint for IRS phase shifts, we utilize a sequential rank-one constraint relaxation (SROCR) algorithm. In addition to single antenna URs scenario, we investigate multi-antenna URs scenario and evaluate their performance. Simulation results validate the effectiveness of using IRS.

A Learning-Aided Intermittent Cooperative Jamming Scheme for Nonslotted Wireless Transmission in an IoT System

The boom of the Internet of Things (IoT) has exposed many security issues in recent years. Cooperative jamming, including the continuous jamming strategy (CJS) and intermittent jamming strategy (IJS), is an effective approach toward secure wireless communication in the physical layer. CJS used to be a primary physical-layer security technology that sends cooperative jamming signals at the expense of energy consumption. Different from CJS, IJS is more energy efficient. The feasibility of IJS has been proved in a slotted scenario, which motivates us to design IJS in a nonslotted scenario. In this article, we discuss the feasibility of IJS for a nonslotted transmission IoT system and formulate an optimization problem based on a sense-harvest-jam policy. This problem is to find the optimal matching precision between durations of artificial noise and legitimate signals. To solve this problem, we exploit a backpropagation-neural-network model to analyze jamming duration proportion and derive the optimal proportion for the binary phase-shift keying modulation. Finally, we design a matching precision optimization algorithm to achieve the optimal nonslotted secure transmission. Simulation results on jamming efficiency demonstrate that the proposed IJS has preferable secure performance than the CJS under energy constraints.

Secrecy Outage Analysis of CR-SWIPT Networks With Artificial Noise and Spatially Random Secondary Terminals

In this paper, the secrecy outage performance of cognitive radio (CR) systems with simultaneous wireless information and power transfer (SWIPT) is investigated, in which non-colluding eavesdroppers (Eves) are randomly located in a 2-dimensional disk and artificial noise is added to safeguard the secrecy performance of the targeted information delivery in the secondary network. The secondary users coexist with primary users in the same bands while the secondary user transmitter (SU-TX) transmits confidential messages to a legitimate receiver (Bob) and energy to multiple energy-receivers (ERs) via the same radio frequency signals. Apart from harvesting energy, these ERs may act as Eves to overhear the confidential information only for Bob. SU-TX equipped with multiple antennas performs beamforming to Bob, which is equipped with multiple antennas and adopts selection combining (SC) scheme. To enhance the secure performance of the considered CR-SWIPT system, SU-TX adds artificial noise (AN) to the original signal designed for Bob according to the instantaneous channel state information (CSI) between SU-TX and Bob, where the artificial noise and original signals for Bob are orthogonal so that Bob can cancel this noise. On ERs’ side, the total received energy for harvesting is not degraded, and a lower signal-to-interference-plus-noise ratio for eavesdropping on the information between SU-TX and Bob is introduced. The approximated closed-form expression for the secrecy outage probability (SOP) is derived by using Gauss-Laguerre quadrature, as well as the asymptotic results are valid in the high signal to noise ratio region. Finally, Monte-Carlo simulations are presented to validate the correctness of the derived analytical results.

Deep Neural Network-Based Precoder for Fairness Aware Secure NOMA Scheme

This work proposes an artificial noise (AN)-aided secure multiple-input single-output non-orthogonal multiple access (NOMA) scheme. In the design of the proposed scheme, we consider fairness that all the users have higher secrecy rates as compared to those given by a competing orthogonal multiple access (OMA) scheme. Despite its importance, the fairness aware design has remained rarely touched since it is mathematically intractable. This work shows that this problem can be efficiently solved by utilizing a deep neural network as the precoder for the information and AN signals even without resorting to some assumptions such as a large antenna array and/or a high signal-to-noise ratio. We will also propose an adaptive mode that switches the access protocol from the OMA scheme to the NOMA scheme only when the fairness is met. Performance of the proposed secure NOMA scheme will be extensively evaluated and compared with existing NOMA and OMA schemes. The comparisons clearly show that the sum secrecy rate can be significantly improved while guaranteeing the fairness, which however cannot be achieved with the existing NOMA scheme.

DNN-Powered SIC-Free Receiver Artificial Noise Aided Terahertz Secure Communications With Randomly Distributed Eavesdroppers

Despite the narrowbeam nature of Terahertz (THz) communications, the physical layer security in the THz band is challenging when eavesdroppers are inside the beam radiation sector. In this paper, a deep neural network (DNN)-based self-interference cancellation (SIC)-free receiver artificial noise (AN) assisted mechanism is proposed to address the in-beam security challenge, by considering randomly distributed eavesdroppers in THz secure communications. By exploiting the different temporal broadening effects of the AN signals at distinct distances, the SIC can be saved with a proper signal detection design rather than using conventional high-complexity cancellation techniques. To combat the non-linearity and non-convexity of the optimization problem, the system parameters including carrier frequency, power of transmission signal and AN signal power, and frame time are designed by an efficient deep neural network (DNN) algorithm to minimize the secrecy outage probability. Numerical results demonstrate that the maximum secrecy rate of our proposed DNN-powered SIC-free receiver AN scheme is up to 3.3 bps/Hz over 10 m transmission when the eavesdropper is in close proximity. Moreover, the secrecy outage probability is less than 0.5% when the eavesdropper density is 0.001 per square meter, which is approximately 33% lower than that of conventional transmitter AN schemes.

Secure Transmission in Massive MIMO System With Specular Component-Based Beamforming and Artificial Noise Over Ricean Fading Channel

This letter investigates the secure transmission in a multi-user massive MIMO system over Ricean fading channel in the presence of a multi-antenna eavesdropper. In order to reduce the system complexity and the channel estimation overhead, a low-complexity beamforming (BF) scheme using only the specular component is presented. Moreover, the generation of artificial noise (AN) is employed at the base station (BS) for additional security enhancement. Specifically, a tractable closed-form lower bound for the achievable ergodic secrecy rate is derived. Furthermore, the optimal power allocation factor between the transmit data power and AN signal power with fixed total power limit is obtained based on the asymptotic analysis to maximize the achievable ergodic secrecy rate. The analytical results reveal that the ergodic secrecy rate improves with the increase of Ricean <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${K}$ </tex-math></inline-formula> -factor and converges to a specific constant when increasing the number of antennas at the BS. The performance of the proposed scheme is evaluated through comprehensive simulations.

Robust 3D-Trajectory and Time Switching Optimization for Dual-UAV-Enabled Secure Communications

This paper investigates a dual-unmanned aerial vehicle (UAV)-enabled secure communication system, in which, a UAV moves around to send confidential messages to a mobile user while another cooperative UAV transmits artificial noise signals to confuse malicious eavesdroppers. Both UAVs have energy constraints and the location information of eavesdroppers is imperfect. We consider a worst-case secrecy rate maximization problem of the mobile user over all time slots. This optimization problem is solved by jointly designing the three-dimensional (3D) trajectory of UAVs and the time allocation (recharging and service or jamming) under practical constraints including maximum UAV speed, UAV collision avoidance, UAV positioning error, and UAV energy harvesting. Specifically, we adopt a more practical UAV-ground channel model with both large-scale and small-scale fading components. Due to the non-convex feasible region constructed by the complicated constraints, directly finding the optimal solution of the original problem is intractable. To address this issue, we decouple the original optimization problem into three subproblems and develop an iterative algorithm to find its suboptimal solution by using the block coordinate descent technique. To solve each subproblem, certain advanced optimization tools, such as integer relaxation, S-procedure, and successive convex approximation techniques, are utilized. Numerical simulation results are provided to corroborate the theoretical derivations and to evaluate the performance of the proposed algorithm. Additionally, the numerical results assist to draw new insights on the 3D UAV trajectory by comparing the performance with conventional two-dimensional (2D) schemes.

Cooperative Transmission of Wireless Information and Energy in Anti-Eavesdropping UAV Relay Network

Aims at the problem of UAV(unmanned aerial/air vehicle) wireless communication network interference signal, physical layer security and energy efficiency, a cooperative transmission scheme of wireless information and energy in the anti-eavesdropping UAV relay network based on interference alignment and power splitting is proposed. UAV relays to send artificial noise interference to interrupt eavesdropping, and filter out the effects of artificial noise and interference signals through distributed interference alignment at the receiving end. At the same time, the UAV antenna is equipped with a power divider to collect energy while receiving signals Increase the UAV relays life time without affecting normal communication. The feasibility analysis of the network was carried out, and the influence of transmitted noise and nontransmitted noise on network performance and eavesdroppers was compared. At the same time, the influence of different segmentation ratios on energy collection efficiency and communication and speed was analyzed.

Artificial Noise Assisted In-Band Full-Duplex Secure Channel Estimation

This paper proposes a novel secure channel estimation technique to provide security against leakage of the channel estimates to any malicious user by utilizing artificial noise (AN) along with full-duplex (FD) transmissions. AN overcomes the drawback of FD transmission, where any strategically located eavesdropper can minimize the interference signal received from the FD receiver. The proposed secure channel estimation technique comprises three stages, where the first stage is responsible for the estimation of the residual self-interference (SI) channel. The second stage acquires rough channel estimates to design AN orthogonal to the channel between legitimate transmitter-receiver for the next training stage. In the third stage, both legitimate nodes transmit orthogonal AN signals along with the known training signals using FD transmissions. For power allocation, we have presented a novel local adaptive power allocation algorithm at each legitimate node to allocate the powers to the training signals, and AN signals while ensuring equivocation at the eavesdropper. We provide the mean square error (MSE) to indicate the performance achieved by the respective nodes. We have also provided the bit error rate (BER) simulation analysis to indicate the secure communication achieved by securing the channel estimation process. The presented simulation analysis indicates that the eavesdropper is unable to decode the transmitted information while the legitimate receiver has robustly decoded the transmitted information.

Design of the Power and Dimension of Artificial Noise for Secure Communication Systems

In this paper, the dimension of artificial noise (AN) and corresponding transmit power in multiple-input multiple-output single-eavesdropper channels are investigated. It is widely known that AN is transmitted in the null space of the channel matrix of a legitimate link between a source and a destination. Here, the secrecy outage probabilities are derived for various dimensions of AN. Recognizing the fact that the secrecy outage performance depends on the dimension of the AN, an optimization problem is formulated to maximize the secrecy rate under a secrecy outage constraint. The optimal power splitting factor between the information and AN signals is then derived. Furthermore, the asymptotic behaviors of the optimal power splitting factor and the resulting maximum secrecy rate are examined. Through asymptotic analyses and numerical verification, it is formally shown that the full-dimension AN maximizes the secrecy rate under a secrecy outage constraint. Because the complexity of AN design increases as the dimension of the AN increases, we can achieve a tradeoff between secrecy performance and AN design complexity by determining the dimension of the AN. This study can provide a guideline of AN design specifically pertaining to the dimension of the AN.

Beamforming Aided Secrecy Energy Efficiency Maximization in Heterogeneous Cellular Networks

This paper investigates the secrecy energy efficiency (SEE) for a two-tier heterogeneous cellular network having a macro cell and multiple small cells, where the macro cell consists of a macro base station (MBS), a macro user and an eavesdropper and meanwhile each small cell comprises of a small base station (SBS), a small user and an eavesdropper. We consider the use of artificial noise (AN) signals emitted at MBS and SBSs at the expense of transmit power to defend against eavesdroppers. For the sake of obtaining a better balance between the secrecy rate (SR) and energy efficiency of heterogeneous cellular networks, we propose an SEE maximization (SEEM) scheme in small cells through jointly optimizing the beamformers of confidential signals and AN at MBS and SBSs, called joint beamforming based SEEM (JBF-SEEM) while guaranteeing the SR requirements and the power constraints for MBS and each SBS. However, the proposed JBF-SEEM problem is a complicated optimization problem because of the non-convex fractional form. Thus, we firstly transform the original objective function in fractional form into a subtractive one through applying the Dinkelbach's method, and then the non-convex subtractive form is approximated into a convex optimization problem by combining the penalty function and the difference of two-convex functions approach. Furthermore, we propose a two-tier iterative JBF-SEEM algorithm to obtain the near-optimal beamforming solution. Numerical results show that the JBF-SEEM algorithm is convergent while achieving a better SEE performance than conventional approaches.

Secrecy analysis of short-packet transmissions in ultra-reliable and low-latency communications

In this paper, we investigate the secrecy performance of short-packet transmissions in ultra-reliable and low-latency communications (URLLC). We consider the scenario where a multi-antenna source communicates with a single-antenna legitimate receiver requiring ultra-high reliability and low latency, in the presence of a single-antenna eavesdropper. In order to safeguard URLLC, the source transmits the artificial noise (AN) signal together with the confidential signal to confuse the eavesdropper. We adopt a lower bound on the maximal secrecy rate as the secrecy performance metric for short-packet transmissions in URLLC, which takes the target decoding error probabilities at the legitimate receiver and the eavesdropper into account. Using this metric, we first derive a compact expression of the generalized secrecy outage probability (SOP). Then, we formally prove that the generalized SOP is a convex function with respect to the power allocation factor between the confidential signal and the AN signal. We further determine the optimal power allocation factor that minimizes the generalized SOP. The results presented in this work can be useful for designing new secure transmission schemes for URLLC.

RIS-Aided Physical Layer Security With Full-Duplex Jamming in Underlay D2D Networks

This paper investigates the physical layer security and data transmission for the underlay device-to-device (D2D) networks, and considers a combination of the reconfigurable intelligent surface (RIS) and full-duplex (FD) jamming receiver for the robustness and security enhancements of the system. In the demonstrated spectrum sharing setup, the total power of the D2D networks is conceived to the transmitter and receiver to transmit a private message and emit the artificial noise (AN) signals. To prevent information leakage, a beamforming design is presented for a multi-antenna FD D2D receiver in order to suppress and inject the AN signals in the direction of legitimate users and eavesdropper, respectively. The statistical characterization of end-to-end RIS-assisted wireless channels is presented, and the achievable ergodic secrecy rate of the system is derived in novel approximate expressions. The numerical and simulation results confirm the accuracy and effectiveness of the proposed analytical framework. The results demonstrate an optimal selection of the D2D power allocations for different number of reflecting elements in terms of achievable ergodic secrecy rates of the system.

Q-Learning-Based Power Allocation for Secure Wireless Communication in UAV-Aided Relay Network

Unmanned aerial vehicle (UAV)-aided wireless relay networks are at risk of eavesdropping activities due to their open nature. In this paper, we study the security of a UAV-aided selective relaying wireless network in which $N$ UAVs are employed as decode-and-forward (DF) relays linking a ground base station (BS) with $L$ legitimate users on the ground in the presence of a passive eavesdropper ( $Eave$ ). Direct links between the ground BS and both the ground users and the eavesdropper are assumed to be blocked. The ground-to-air and air-to-ground channels are assumed to follow Rician fading model with opportunistic scheduling scheme for UAVs and users selection. In order to secure data transmissions against such an interception action, the UAV of the worst UAV-selected user link transmits a jamming artificial noise (AN) signal to degrade $Eave$ ability in decoding the confidential information successfully. The transmission outage probability, intercept probability, and hybrid outage probability are derived and analyzed. Due to the heavy computation burden raised by increasing the number of UAVs and users as well as the difficulty in estimating the instantaneous channel state information (CSI), existing traditional optimization methods are not highly efficient in solving the considered power allocation problem. Therefore, we propose a dynamic power control scheme based on Q-learning algorithm combined with statistical CSI where the hybrid outage probability is minimized. Simulation results show that the proposed algorithm efficiently reduces the hybrid outage probability with a noticeable reduction in the computational time.