To satisfy the communication, localization, and energy demands of low-power IoT nodes, combining integrated sensing and communication (ISAC) and simultaneous wireless information and power transfer (SWIPT) can offer an innovative solution. However, carrying private information in wireless sensing beams critically increases the vulnerability of being eavesdropped by the target. In this paper, we propose a non-orthogonal multiple access (NOMA)-enhanced secure transmission strategy to counteract the internal eavesdropping for SWIPT-ISAC. We jointly optimize the transmit beamforming and power splitting to maximize the secrecy rate towards the eavesdropping by the target, ensuring the nonlinear energy harvesting (EH) and precise sensing beampatterns. Our approach enables the nodes to manage the interference through successive interference cancellation and to harvest energy from the transmitted signal. The original optimization problem is non-convex and difficult to tackle. Using the semidefinite relaxation, we convert it to convex form, and propose alternating optimization algorithm to derive the solutions. Simulation results indicate that the proposed scheme can effectively counteract the internal eavesdropping, while ensuring the nonlinear$\mathbf{E H}$and sensing performance.

As unmanned aerial vehicles (UAVs) increasingly operate in large-scale clusters, traditional routing protocols struggle to ensure efficient and time-sensitive packet path planning due to the growing network size and inherent mobility of UAVs. Meanwhile, despite deep learning (DL) based routing methods have shown promise in small UAV networks, their computational demands and limited scalability to large numbers of UAV nodes pose significant challenges. To address the challenges of scalability and computational demands in large-scale UAV networks, this paper proposes a novel decentralized global guided routing algorithm based on potential field. First, a potential field is constructed using a harmonic function to represent the current network status. Subsequently, leveraging this potential field, a global route is derived to define the overarching direction for data transmission. Finally, a compact neural network deployed at each node utilizes the global guidance direction and the local potential field information obtained from its surroundings to establish a specific data forwarding path within its maximum perception range. Simulation results illustrate the advantages of our proposed approach for establishing UAV paths in large-scale UAV networks.

The openness of wireless communication poses significant privacy risks to systems enabled by unmanned aerial vehicle (UAV). In this paper, we investigate multi-antenna UAV-enabled covert communication system against an uncertainly located ground warden. The location-uncertain warden presents a heightened challenge to covert communication. We propose an effective scheme to deal with the covert communication against uncertainly located warden. In the first stage, we consider the worst-case scenario, assuming the warden is in the ideal detection threshold and the optimal position. First, we derive the ideal threshold and then use sequential quadratic programming (SQP) algorithm to determine the optimal position. In the second stage, we enhance the performance of UAV-enabled covert communication with SQP algorithm by jointly optimizing the transmission rate, transmission power, and artificial jamming power of full-duplex receiver. Our simulation results demonstrate that covert communication is achievable in the location-uncertain scenario through the proposed scheme.

To satisfy the communication, localization, and energy demands of low-power IoT nodes, combining integrated sensing and communication (ISAC) and simultaneous wireless information and power transfer (SWIPT) can offer an innovative solution. However, carrying private information in wireless sensing beams critically increases the vulnerability of being eavesdropped. In this paper, we propose two non-orthogonal multiple access (NOMA)-enhanced secure transmission strategies to counteract the internal and external eavesdropping for SWIPT-ISAC. First, we jointly optimize the transmit beamforming and power splitting to maximize the secrecy rate towards the internal eavesdropping by the target, ensuring the nonlinear energy harvesting (EH) and precise sensing beampatterns. Then, facing a more severe scenario with L external eavesdroppers, we exploit the artificial jamming with the highest power allocation to mitigate both the internal and external eavesdropping. Our approach enables the nodes to manage the interference through successive interference cancellation and to harvest energy from the jamming. The original optimization problems in both scenarios are non-convex and difficult to tackle. Using the semidefinite relaxation, we convert them to convex forms, and propose alternating optimization algorithms to derive the solutions. Simulation results indicate that the proposed schemes can effectively counteract the internal and external eavesdropping, while ensuring the nonlinear EH and sensing performance.

Integrated sensing and communication (ISAC), by combining the communication and sensing functions in shared frequency bands, emerges as a promising technology for future wireless networks. However, the performance of ISAC may be affected by the channel fading and massive connections. In this paper, we propose a non-orthogonal multiple access (NOMA) aided ISAC scheme via intelligent reflective surface (IRS) to set up virtual line-of-sight links for multi-user communication and target sensing. Specifically, our goal is to maximize the sum rate through the joint optimization of active transmit beamforming at the base station and passive phases for reflecting at the IRS, while satisfying the sensing requirement for the target user. Since the original optimization problem is non-convex, we first decompose it into two subproblems, which are converted into convex ones by applying the successive convex approximation. Then, an alternating optimization algorithm is proposed to derive a solution to the original problem. Simulation results validate that the proposed scheme can effectively enhance the multi-user NOMA communication performance while guaranteeing the sensing quality by introducing IRS.

Integrated sensing and communication (ISAC), as an emerging technology for 6G, raises a critical security issue that the sensing waveform may expose the private information to suspicious detection targets. In this paper, we design to utilize intelligent reflecting surface (IRS) in ISAC to enhance the secure transmission for non-orthogonal multiple access nodes, and establish an additional line-of-sight link for the detection. An IRS-aided secure transmission scheme is proposed to jointly optimize the jamming, the active transmit precoding at the base station and the passive phase reflecting at the IRS to maximize the sum secrecy rate, subject to the echo signal requirement towards the target. To address the non-convexity of the proposed problem, it is decomposed into two subproblems, enabling the optimization of the transmit jamming and precoding vectors and the phase reflecting matrix, respectively. Then, with the help of successive convex approximation, these subproblems are derived to be convex, and an alternating optimization algorithm is introduced to address the original problem. Simulations verify that the proposed scheme significantly outperforms the benchmarks, and can guarantee the sensing functioning while greatly enhancing the communication security.

Integrated sensing and communication (ISAC) systems can suffer from malicious jamming attacks due to the open nature of wireless channels. Deploying aerial intelligent reflecting surface (AIRS) can flexibly configure the propagation environment of ISAC to address this threat. In this paper, we propose an anti-jamming scheme for ISAC via AIRS. Our goal is to maximize the achievable sum rate by jointly optimizing the transmitting beamforming at the dual-function base station, as well as the phase shift matrix and deployment of AIRS, while satisfying the echo signal-to-interference-plus-noise ratio requirement of target sensing. To handle this non-convex problem with multiple coupled variables, we decompose it into three sub-problems and solve them via the alternate optimization. We first introduce auxiliary variables to convert the transmit beamforming sub-problem into a convex counterpart and solve it via semi-definite relaxation. Then, the IRS phase-shift design is transformed into an equivalent rank-constrained problem, and the penalty-based method and the first-order Taylor expansion are leveraged to calculate the passive beamforming. Finally, with the optimized active and passive beamformings, we resort to successive convex approximation to optimize the AIRS deployment. Simulation results are presented to verify the feasibility and effectiveness of the proposed scheme.

Integrated sensing and communication (ISAC), as an emerging technology for 6G, raises a critical security issue that the sensing waveform may expose the private information to suspicious detection targets. In this paper, we design to utilize intelligent reflecting surface (IRS) in ISAC to enhance the secure transmission for non-orthogonal multiple access nodes, and establish an additional line-of-sight link for the detection. An IRS-aided secure transmission scheme is proposed to jointly optimize the jamming, the active transmit precoding at the base station and the passive phase reflecting at the IRS to maximize the sum secrecy rate, subject to the echo signal requirement towards the target. To address the non-convexity of the proposed problem, it is decomposed into two subproblems, enabling the optimization of the transmit jamming and precoding vectors and the phase reflecting matrix, respectively. Then, with the help of successive convex approximation, these subproblems are derived to be convex, and an alternating optimization algorithm is introduced to address the original problem, which is guaranteed to converge. Simulations verify that the proposed scheme significantly outperforms the benchmarks, and can guarantee the sensing functioning while greatly enhancing the communication security.

In this paper, an anti-jamming design for integrated sensing and communication (ISAC) via aerial intelligent reflecting surface (AIRS) is proposed. We aim to maximize the achievable sum rate by jointly optimizing the active and passive beamformings, as well as the deployment of AIRS, while satisfying the echo signal-to-interference-plus-noise ratio requirement of target sensing. To address the non-convex problem, we decompose it into three sub-problems and solve them via the alternate optimization. First, the active beamforming is calculated via semi-definite relaxation. Then, the penalty-based method and the first-order Taylor expansion are leveraged to solve the passive beamforming. With the optimized active and passive beamformings, we resort to successive convex approximation to optimize the AIRS deployment. Numerical results validate the effectiveness of the proposed scheme.

Rate-splitting multiple access (RSMA) is an emerging multiple access strategy, with non-orthogonal multiple access (NOMA) and space division multiple access (SDMA) as its two special cases. RSMA divides the messages required by users into the private and common parts, and the private streams are naturally suitable for the secure transmission. In this paper, we establish a unified rate-splitting framework to ensure the secure transmission for the three multiple access systems mentioned above. The precoders at the multi-antenna transmitter are conjointly optimized to improve the transmission rate of common message. Successive interference cancellation (SIC) is utilized, and the private message for the downlink broadcasting RSMA network can be effectively hidden in the high-power common message. Simulation results demonstrate that the proposed rate-splitting framework can effectively guarantee the secure transmission of the secrecy information.

Integrated sensing and communication (ISAC) is an up-and-coming technique for future 6G networks. However, the communication message carried by the detection waveform will face the risk of being eavesdropped, which leads to the challenge of wireless security for ISAC networks. In this paper, we leverage non-orthogonal multiple access (NOMA) to support more users for the ISAC network, with the precoding well designed to guarantee the security. Specifically, we formulate a joint precoding optimization problem to maximize the sum secrecy rate for multiple users via artificial jamming, where the superimposed signal for NOMA users can be concurrently employed for the target detection. Since the optimization problem is non-convex, it is transformed into a convex one based on successive convex approximation (SCA), where the Taylor’s approximation and second-order cone (SOC) constraint are further applied. Then, we propose an iterative algorithm, through which the original optimization problem can be solved effectively. Simulation results show that the proposed secure NOMA-ISAC scheme can guarantee the secure transmission while ensuring the sensing performance.

Non-orthogonal multiple access (NOMA) is an important technology for the forthcoming 5G and beyond. However, its privacy often suffers from adversarial eavesdropping, especially for the users with higher transmit power. In this paper, we propose a jamming-aided secure transmission scheme for cooperative NOMA networks with a full-duplex (FD) relay. In this scheme, two pairs of users perform secure transmission with the help of a decode-forward (DF) relay, which forwards information and generates artificial jamming to counteract eavesdropping. The precoding vectors are designed to zero-force the artificial jamming at legal receivers. Then, the channel statistics are calculated, based on which the expressions of secrecy outage probability (SOP) are derived. Simulation results show the accuracy of our analysis, and demonstrate that the proposed scheme can effectively reduce the SOP and improve the effective secrecy throughput via artificial jamming and FD relaying.

Non-orthogonal multiple access (NOMA) is a prospective technology for radio resource constrained future mobile networks. However, NOMA users far from base station (BS) tend to be more susceptible to eavesdropping because they are allocated more transmit power. In this paper, we aim to jointly optimize the precoding vectors at BS to ensure the legitimate security in a downlink multiple-input single-output (MISO) NOMA network. In the proposed scheme, we can maximize the sum secrecy rate by joint precoding optimization. Owing to its non-convexity, the problem is converted into a convex one, which is solved by a second-order cone programming based iterative algorithm. Simulation results are presented to demonstrate that the proposed schemes can improve the security performance for MISO NOMA systems effectively.