Channel State Information Of Eavesdropper Research Articles

Hybrid Beamforming for Secure Transmission of Massive MIMO UAV Communication Networks

The powerful line-of-sight (LoS) characteristic between unmanned aerial vehicles (UAV) and terrestrial nodes could be leveraged by large-scale antenna arrays to significantly increase transmission rates, while the problem of secure transmission is emerging. Compared with fully digital beamforming, hybrid beamforming (HBF) could meet a compromise between cost and performance, which is precisely optimized in this article to maximize the secrecy rate of massive multiple-input–multiple-output (MIMO) UAV communication network. At first, we propose a secure HBF framework based on generalized eigenvalue decomposition and singular value decomposition. After that, considering the difficulty in directly solving the HBF optimization problem, an iterative algorithm based on successive convex approximation is developed for perfectly known channel state information (CSI). Furthermore, while CSI is imperfect, a neural network is constructed and trained to learn the statistical characteristics of wireless channels and complete the design of hybrid beamformer and combiner simultaneously. Performance validation and beampattern of the proposed HBF methods are given by extensive simulation results, which demonstrate the proposed secure HBF framework could considerably improve secrecy rate, and the deep learning-based HBF method possesses a positive average secrecy rate even with unknown eavesdropper's CSI.

Cooperative jamming aided securing wireless communications without CSI of eavesdroppers

Physical layer security was designed as an effective solution to provide the security and confidentiality of information transmission in wireless networks, and secrecy transmission capacity (STC) played a key role in analyzing the impact of system parameters on physical layer security. Different from the previous works, which exploited cooperative jamming to improve the security with the assumption of perfect channel state information (CSI) of eavesdroppers (Eves), in this paper, without considering Eves’ CSI, we designed two secrecy improvement strategies aided by cooperative jamming with transmit power allocation scheme, i.e., connection guard zone (CGZ) and improved interferer protected zone (IIPZ). Specifically, we established an analytical framework of the STC by applying the tools of stochastic geometry and derived conditions that achieved a positive STC. In addition, we consider the impact of Random WayPoint (RWP) mobile receiver and active eavesdroppers on physical layer security. Simulations showed that IIPZ achieves the best reliability performance and CGZ makes the best secrecy performance than existing popular protections, and RWP mobile destination can achieve a higher level of reliability and STC than these achievable in static scenarios.

Deep Reinforcement Learning Based UAV for Securing mmWave Communications

This paper focuses on the unmanned aerial vehicle (UAV) enabled millimeter (mmWave) communications from physical layer security perspective. A UAV is arranged as an aerial base station to provide ubiquitous connectivity for terrestrial users in the presence of multiple eavesdroppers. With statistical channel state information (CSI) of eavesdroppers, the beamforming vector and trajectory of UAV as well as user scheduling are jointly optimized to minimize the weighted sum of UAV flight period and secrecy outage duration. The considered problem is a combinatorial optimization problem with complicated objective function, and thus difficult to be solved by convex optimization-based methods. To this end, we formulate this problem as a Markov decision process (MDP) and develop a deep reinforcement learning (DRL) based method to optimize all variables simultaneously. Simulation results validate superiority of the proposed method over benchmarks and demonstrate its ability to obtain a compromise between secure transmission and energy efficiency.

STAR-RIS Enabled Downlink Secure NOMA Network Under Imperfect CSI of Eavesdroppers

Reconfigurable intelligence surface (RIS) is regarded as one of the key technologies for the future wireless communications. Recently, simultaneous transmission and reflection (STAR) RIS is proposed to overcome the geographical constraint of the conventional reflection only RIS. In this letter, we model the STAR-RIS enabled downlink secure non-orthogonal multiple access systems under imperfect channel state information (CSI) of eavesdroppers. Specifically, we propose the block coordinate descent based optimization framework to maximize the worst secrecy rate with active beamforming of downlink NOMA at the base station and STAR-RIS coefficients, where the uncertainty of eavesdropper’s CSI is transformed by S-Procedure. The successive convex approximation and a penalty-based method are utilized to address the non-convexity of the problem. Finally, simulation results demonstrate that the worst secrecy rate of the proposed algorithm outperforms that of the conventional RIS and the other benchmark schemes.

Robust and Secure Resource Allocation for ISAC Systems: A Novel Optimization Framework for Variable-Length Snapshots

In this paper, we investigate the robust resource allocation design for secure communication in an integrated sensing and communication (ISAC) system. A multi-antenna dual-functional radar-communication (DFRC) base station (BS) serves multiple single-antenna legitimate users and senses for targets simultaneously, where already identified targets are treated as potential single-antenna eavesdroppers. The DFRC BS scans a sector with a sequence of dedicated beams, and the ISAC system takes a snapshot of the environment during the transmission of each beam. Based on the sensing information, the DFRC BS can acquire the channel state information (CSI) of the potential eavesdroppers. Different from existing works that focused on the resource allocation design for a single snapshot, in this paper, we propose a novel optimization framework that jointly optimizes the communication and sensing resources over a sequence of snapshots with adjustable durations. Besides, artificial noise (AN) is exploited by the BS for joint sensing and physical layer security provisioning. To this end, we jointly optimize the duration of each snapshot, the beamforming vector, and the covariance matrix of the AN for maximization of the system sum secrecy rate over a sequence of snapshots while guaranteeing a minimum required average achievable rate and a maximum information leakage constraint for each legitimate user. The resource allocation algorithm design is formulated as a non-convex optimization problem, where we account for the imperfect CSI of both the legitimate users and the potential eavesdroppers. To make the problem tractable, we derive a bound for the uncertainty region of the potential eavesdroppers’ small-scale fading based on a safe approximation, which facilitates the development of a block coordinate descent-based iterative algorithm for obtaining an efficient suboptimal solution. Simulation results illustrate that the proposed scheme can significantly enhance the physical layer security of ISAC systems compared to three baseline schemes. Moreover, compared to the conventional multi-stage approach for ISAC system design, the proposed approach based on variable-length snapshots not only facilitates a highly-directional offline sensing beam design but also allows us to flexibly prioritize communication or sensing depending on the application scenario.

Optimization of pre-equalized time reversal security transmission systems assisted with artificial noise

Time reversal (TR) transmission technology can focus the power of a signal in both time and space domains and reduce signal energy leakage to unintended receivers, making it suitable for physical layer security systems. By adding a pre-equalizer to the transmitter and optimizing it, the performance of multi-antenna TR transmission system can be improved obviously with an acceptable optimization complexity. In this paper, the pre-equalizer and artificial noise (AN) are jointly optimized to improve the security performance of pre-equalized TR (ETR) systems when eavesdropping channel state information (ECSI) is unknown or known. When ECSI is unknown, null-space AN is adopted, and the pre-equalizer is optimized to minimize the signal power under the constraint of the minimum signal-to-interference-plus-noise ratio (SINR) of the legitimate receiver, so the AN power and the interference with the eavesdropper are maximized. The optimization problem is transformed into the problem of finding the maximum generalized eigenvalue of a matrix pencil. When ECSI is known, under the minimum SINR constraint of the legitimate receiver, the pre-equalizer and AN’s covariance matrix are jointly optimized to minimize the SINR of the eavesdropper. The optimization problem is non-convex and is transformed into a convex problem, which can be solved using the CVX toolbox. The optimization complexity is independent of the number of transmit antennas. Simulation results demonstrate that compared with TR systems, by optimizing the pre-equalizer, the security performance of ETR multi-antenna systems can be significantly improved, and the optimization complexity is acceptable.

RIS-assisted MIMO secure communications with Bob's statistical CSI and without Eve's CSI

In this paper, we consider a reconfigurable intelligent surface (RIS)-assisted multiple-input multiple-output (MIMO) secure communication system, where only legitimate user's (Bob's) statistical channel state information (CSI) can be obtained at the transmitter (Alice), while eavesdropper's (Eve's) CSI is unknown. Firstly, the analytical expression of the achievable ergodic rate at Bob is obtained. Then, by exploiting Bob's statistical CSI, we jointly design the transmit covariance matrix at Alice and the phase shift matrix at the RIS to minimize the transmit power of the information signal under the quality-of-service (QoS) constraint of Bob. Finally, we propose an artificial noise (AN)-aided method without Eve's CSI to enhance the security of this system and use the residual power to design the transmit covariance for AN. Simulation results verify the convergence of the proposed method, and also show that there exists a trade-off between the secrecy rate and QoS of Bob.

Securing Intelligent Reflecting Surface Assisted Terahertz Systems

This paper focuses on securing confidential communication in multiple intelligent reflecting surfaces (IRS) assisted terahertz (THz) systems, where a potential eavesdropper can intercept either the base station (BS)-IRS link or the IRS-user link. Notably, the secure transmission may be intercepted and blocked by the eavesdropper due to the blockage-prone nature in THz bands. To characterize the blocking effects of the eavesdropper, the blocking-based path loss is first investigated. With the imperfect eavesdropper channel state information (ECSI), the worst-case secrecy rate (WCSR) is derived, and a joint optimization problem of hybrid beamforming at the BS and reflecting beamforming at the IRS is formulated. For the BS-IRS link eavesdropping, the zero-forcing (ZF) principle-based hybrid beamforming and the closed-form phase shifts of multiple IRSs are respectively proposed. For the IRS-user link eavesdropping, an iterative algorithm is proposed to tackle the non-convex optimization problem with a given information leakage threshold. Finally, a robust secure transmission strategy for multi-eavesdropper systems is further investigated. Simulation results demonstrate that compared with blockage-unaware scenarios, our proposed scheme can resist the adverse effects of the blockage-prone nature of THz waves on information security, and significantly boost secrecy performance.

Secure Downlink Transmission in Cell-Free Massive MIMO System Enhanced by Intelligent Reflecting Surfaces

This paper presents the application of intelligent reflecting surfaces (IRSs) in a cell-free massive MIMO network to enhance secure transmission in the system. Multiantenna access points (APs) need to transmit information to users safely and reliably via IRSs without fully knowing the channel state information (CSI) of a multiantenna eavesdropper (Eve) or the accurate beamforming information of a jammer. Specifically, through joint optimization of the AP active beamforming (ABF) and IRS passive beamforming (PBF), the information leaked to the Eve is limited by a set threshold, and restrictions on the IRS reflection phase are considered to maximize the weighted sum rate of the system’s downlink transmission. To solve this multivariate-coupled nonconvex problem, we propose a joint precoding framework under imperfect CSI, using the generalized S-procedure, fractional programming (FP), and multidimensional complex quadratic transformation (MCQT) to transform the original complex nonconvex problem into an easily solvable convex optimization problem, and an alternating algorithm to obtain the optimal solution for precoding and IRS phase shifting. Simulation results show that the proposed scheme can significantly increase the weighted sum rate of the system compared to conventional antijamming methods while revealing that the scheme is effective in enhancing secure system transmission.

Secure Transmission via IUI Engineering for IRS-Assisted NOMA Systems

Inter-user interference (IUI) engineering is utilized to degrade eavesdropping and enhance the physical layer security (PLS). In this letter, we propose a secure transmission strategy via IUI engineering for an intelligent reflecting surface (IRS)-assisted non-orthogonal multiple access (NOMA) system without eavesdroppers channel state information (CSI). We aim to reduce the signal-to-interference-plus-noise ratio (SINR) of the passive eavesdropper to deteriorate eavesdropping by maximizing the transmit power of weaker users and modifying the successive interference cancelation (SIC) order. Moreover, two cases of combating eavesdropping via IUI engineering are considered according to different channel gain of secure users. The formulated problem is non-convex due to the highly coupled beamformers and reflection coefficients, we employ an alternating optimization (AO) framework to solve it. The results validate the advantages of introducing IUI engineering in the IRS-assisted NOMA system and the effectiveness of this optimization algorithm.

Beamforming and Jamming Optimization for IRS-Aided Secure NOMA Networks

The integration of intelligent reflecting surface (IRS) and multiple access provides a promising solution to improved coverage and massive connections at low cost. However, securing IRS-aided networks remains a challenge since the potential eavesdropper also has access to an additional IRS reflection link, especially when the eavesdropping channel state information is unknown. In this paper, we propose an IRS-assisted non-orthogonal multiple access (NOMA) scheme to achieve secure communication via artificial jamming, where the multi-antenna base station sends the NOMA and jamming signals together to the legitimate users with the assistance of IRS, in the presence of a passive eavesdropper. The sum rate of legitimate users is maximized by optimizing the transmit beamforming, the jamming vector and the IRS reflecting vector, satisfying the quality of service requirement, the IRS reflecting constraint and the successive interference cancellation (SIC) decoding condition. In addition, the received jamming power is adapted at the highest level at all legitimate users for successful cancellation via SIC. To tackle this non-convex optimization problem, we first decompose it into two subproblems, and then each subproblem is converted into a convex one using successive convex approximation. An alternate optimization algorithm is proposed to solve them iteratively. Numerical results show that the secure transmission in the proposed IRS-NOMA scheme can be effectively guaranteed with the assistance of artificial jamming.

Optimal Beamforming for Secure Transmit in Practical Wireless Networks

In real communication systems, secure and low-energy transmit scheme is very important. So far, most of schemes focus on secure transmit in special scenarios. In this paper, our goal is to propose a secure protocol in wireless networks involved various factors including artificial noise (AN), the imperfect receiver and imperfect channel state information (CSI) of eavesdropper, weight of beamforming (BF) vector, cooperative jammers (CJ), multiple receivers, and multiple eavesdroppers, and the analysis shows that the protocol can reduce the transmission power, and at the same time the safe reachability rate is greater than our pre-defined value, and the analysis results are in good agreement with the simulation results. In this letter, the minimal transmit power is modeled as a non-convexity optimization that is general difficult. Our method is to transform it into a two-level non-convex problem. The outer is a univariate optimization that can be solved by the golden search algorithm. The inner is a convex optimization solved by using the CVX. The solutions are further used to improve the confidentiality rate of the system, and reduce the transmit power of the system and resource consumption in terms of the imperfect CSI. Simulations show the efficiency and robustness of the proposed protocol.

Robust secure beamforming algorithm for intelligent reflecting surface-assisted satellite-terrestrial integrated networks

For intelligent reflection surface (IRS) assisted satellite-terrestrial integrated network (STIN), a robust secure beamforming method based on the imperfect channel state information (CSI) of eavesdroppers is proposed. First of all, considering that the satellite uses spot beam technology to serve the earth station, while the ground base station (BS) serves multiple ground users through multicast technology, and in the case of frequency spectrum shared between the two networks, a joint optimization problem is formulated to minimize the total transmit power of STIN while satisfying the quality of service constraints of the BS users and the achievable secrecy rate constraints of the earth station. Secondly, in order to solve this non-convex problem, the upper bound and the lower bound of the eavesdroppers’ output signal-to-noise ratio under the condition of imperfect CSI are derived by employing triangle inequality together with Holder inequality. Then, a joint optimization scheme of robust BF and power control based on semi-positive definite programming and penalty function method is proposed to realize the secure and reliable transmission in STIN. Finally, the simulation results verify the effectiveness and superiority of the proposed algorithm.

Physical Layer Security in an OFDM Time Reversal SISO Communication With Imperfect Channel State Information

A frequency domain time-reversal (TR) precoder is proposed to perform physical layer security in single-input single-output (SISO) systems using orthogonal frequency-division multiplexing (OFDM) and artificial noise (AN) injection. This scheme guarantees the secrecy of a communication towards a legitimate user, Bob, by exploiting the frequency diversity selective behaviour in multipath channels. The transmitter, Alice, has imperfect channel state information (CSI) of the legitimate link thanks to the channel reciprocity in time division duplex systems and does not know the instantaneous CSI of a potential eavesdropper, Eve. Three optimal decoding structures at Eve are considered in a block fading environment depending on the handshake procedure between Alice and Bob. Closed-form approximations of the signal-to-noise ratio required at Bob and the maximal CSI error that can be made at Alice, in order to guarantee a communication ergodic secrecy rate (ESR), are derived. Furthermore, the optimal amount of AN energy to inject, considering imperfect CSI, is also given as a closed-form expression. A trade-off on the choice of the spreading factor of the TR precoder is established between maximizing the ESR and decreasing the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\boldsymbol {\epsilon }-$ </tex-math></inline-formula> achievable secrecy rate. Finally, thanks to these results, Alice can be a priori aware of the ESR over which she can establish a secure communication.

Trust-aware buffer-aided relay selection for secure communications in cooperative wireless systems

Cooperative wireless networks have been facing security challenges due to the inherent openness of wireless channels. Previous studies on the physical layer security (PLS) of cooperative networks mainly focus on scenarios with only trusted relays. In practice, however, untrusted relays may exist in the network and such relays may refuse to cooperate or even work as a helper of an eavesdropper for packets eavesdropping/interception. To address this issue, we consider in this paper a cooperative wireless network with untrusted relays and a passive eavesdropper attempting to wiretap packets transmitted in the network. To select a secure and trusted relay, we first propose two buffer-aided relay selection schemes, one for perfect eavesdropper channel state information (CSI) case and another for no eavesdropper CSI case. We then conduct theoretical analysis to derive the models for the performance metrics of secrecy outage probability (SOP) and expected queuing delay. Finally, simulation and numerical results are provided for the validation of our theoretical models. The results indicate that our proposed schemes can outperform the typical max-ratio scheme under perfect eavesdropper CSI case and can outperform the max-link and the max-max relay selection schemes under no eavesdropper CSI case in terms of the SOP and expected queuing delay.

Robust Hybrid Precoding Design for Securing Millimeter-Wave IoT Networks Under Secrecy Outage Constraint

Hybrid precoding architecture, as a cost-effective approach for millimeter-wave (mmWave) communications, can achieve an excellent tradeoff between spectrum efficiency and hardware implementation complexity. However, the design of a robust hybrid precoding for improving the physical layer security (PLS), which is insensitive to the uncertainty of eavesdropper's channel state information (CSI), has not been well studied. This article for the first time designs a probabilistically robust hybrid precoding scheme for securing broadcast communications in Internet of Things (IoT) with eavesdropper's imperfect CSI. Specifically, considering the Gaussian CSI error model, we maximize the minimum secrecy rate of multiple IoT devices (IoDs) by jointly designing analog and digital precoders under the constraints in terms of secrecy outage probability and per IoD's information rate. The optimization problem is challenging due to the coupling of the analog and digital precoders, and the secrecy outage constraint. To handle these challenges, we first employ a conservative probability inequality to transform the secrecy outage probability constraint into a deterministic one. Then, by employing the penalty dual decomposition (PDD) method, we develop a novel iterative algorithm to convert the resultant nonconvex problem into a sequence of convex problems, which can guarantee the convergence to its Karush-Kuhn-Tucker (KKT) solution. Simulation results show that the proposed algorithm can achieve significant secrecy performance gains compared with the benchmark algorithm.

Buffer-aided relay selection for secure communication in two-hop wireless networks with limited packet lifetime

Buffer-aided relay selection serves as one of the key approaches for achieving physical layer security (PLS) of wireless networks. Existing studies on buffer-aided relay selection mainly concentrate on the scenarios where transmitted packets have unlimited lifetime, while the more practical and important scenarios with limited packet lifetime remain largely unexplored. This paper therefore aims to study the buffer-aided relay selection for achieving PLS in two-hop wireless networks with limited packet lifetime. We first propose a novel buffer-aided relay selection scheme by carefully considering the remaining lifetimes of packets, conditions of available links and channel state information (CSI) of eavesdroppers. To model the security and reliability performances achieved by the proposed scheme, we then apply tools from the Markov chain theory to derive expressions of the secrecy outage probability (SOP) and the packet discarding probability (PDP) of the network, respectively. Finally, extensive simulation and numerical results are provided to illustrate the performances of our proposed scheme and our theoretical framework. The results show that although our scheme achieves a slightly higher SOP than the typical buffer-aided max-link relay selection scheme, it can greatly reduce the PDP of the network.

Outage Constrained Robust Secure Beamforming in Cognitive Satellite-Aerial Networks

This letter proposes a robust beamforming scheme to enhance the physical layer security (PLS) of multicast transmission in a cognitive satellite and aerial network (CSAN) operating in the millimeter wave frequency band. Based on imperfect channel state information (CSI) of both eavesdroppers (Eves) and primary users (PUs), we maximize the minimum achievable secrecy rate (ASR) of the secondary users (SUs) in the aerial network under the constraints of the interference to the PUs in the satellite network, the quality of service (QoS) requirements of the SUs and per-antenna power budget of the aerial platform. To tackle this mathematically intractable problem, we first introduce an auxiliary variable and outage constraints to simplify the complex objective function. We then convert the non-convex outage constraints into deterministic forms and adopt penalty function approach to obtain a semi-definite problem such that it can be solved in an iterative fashion. Finally, simulation results show that with the transmit power increase, the minimal ASR of SUs obtained from the proposed BF scheme well approximate the optimal value.

Improving Physical Layer Security for Reconfigurable Intelligent Surface Aided NOMA 6G Networks

The intrinsic integration of the nonorthogonal multiple access (NOMA) and reconfigurable intelligent surface (RIS) techniques is envisioned to be a promising approach to significantly improve both the spectrum efficiency and energy efficiency for future wireless communication networks. In this paper, the physical layer security (PLS) for a RIS-aided NOMA 6G networks is investigated, in which a RIS is deployed to assist the two "dead zone" NOMA users and both internal and external eavesdropping are considered. For the scenario with only internal eavesdropping, we consider the worst case that the near-end user is untrusted and may try to intercept the information of far-end user. A joint beamforming and power allocation sub-optimal scheme is proposed to improve the system PLS. Then we extend our work to a scenario with both internal and external eavesdropping. Two sub-scenarios are considered in this scenario: one is the sub-scenario without channel state information (CSI) of eavesdroppers, and another is the sub-scenario where the eavesdroppers' CSI are available. For the both sub-scenarios, a noise beamforming scheme is introduced to be against the external eavesdroppers. An optimal power allocation scheme is proposed to further improve the system physical security for the second sub-scenario. Simulation results show the superior performance of the proposed schemes. Moreover, it has also been shown that increasing the number of reflecting elements can bring more gain in secrecy performance than that of the transmit antennas.

Physical Layer Security Assisted Computation Offloading in Intelligently Connected Vehicle Networks

In this paper, we propose a secure computationoffloading scheme (SCOS) in intelligently connected vehicle (ICV) networks, aiming to minimize overall latency of computing via offloading part of computational tasks to nearby servers in small cell base stations (SBSs), while securing the information delivered during offloading and feedback phases via physical layer security. Existing computation offloading schemes usually neglected time-varying characteristics of channels and their corresponding secrecy rates, resulting in an inappropriate task partition ratio and a large secrecy outage probability. To address these issues, we utilize an ergodic secrecy rate to determine how many tasks are offloaded to the edge, where ergodic secrecy rate represents the average secrecy rate over all realizations in a time-varying wireless channel. Adaptive wiretap code rates are proposed with a secrecy outage constraint to match time-varying wireless channels. In addition, the proposed secure beamforming and artificial noise (AN) schemes can improve the ergodic secrecy rates of uplink and downlink channels even without eavesdropper channel state information (CSI). Numerical results demonstrate that the proposed schemes have a shorter system delay than the strategies neglecting time-varying characteristics.