This correspondence reveals the potential of reconfigurable intelligent surface (RIS) in anti-jamming communications. In particular, we consider an aerial RIS (ARIS) that can be flexibly deployed in the air so as to mitigate jamming attacks and enhance the legitimate transmissions. We formulate the joint optimization of ARIS deployment and passive beamforming and solve the problem through an alternating optimization framework, where the location of ARIS is obtained by successive convex approximation and the reflection beamformer is tackled with manifold optimization. Finally, simulation results demonstrate that an ARIS with our proposal can effectively mitigate the jamming attacks and thus safeguard the legitimate transmissions.

In this paper, a novel reconfigurable intelligent surface (RIS)-assisted HAP-UAV secure multi-user mixed radio frequency (RF)/free space optical (FSO) system is proposed. Specifically, the Gamma-Gamma distribution is utilized to characterize the atmospheric turbulence effect for the FSO link from UAV to HAP, while the Rayleigh and Nakagami- m distribution fading are applied to simulate the legitimate and wiretap RF links, respectively. We present the closed-form expressions for the probability density functions, the cumulative distribution functions, and the secrecy outage probability (SOP) of the end-to-end signal-to-noise ratio (SNR) in terms of Meijer’s G-function. To gain more insight into secrecy performance, we further obtain the closed-form expressions for the asymptotic SOP, the asymptotic probability of positive secrecy capacity (PPSC), the diversity gain, and the coding gain at high SNR regions. We can observe that the secrecy performance depends on the weaker channel between the RF and FSO, and is closely related to the number of RIS elements, the number of terrestrial users, the atmospheric turbulence factor, pointing error parameters, and the fading parameter of Nakagami- m distributed wiretap link. Finally, numerical results validate the derived results and demonstrate that the proposed design achieves superior secrecy performance over the benchmarks.

In order to improve the spectrum efficiency and secrecy energy efficiency, in this paper, we propose a nonorthogonal multiple access (NOMA) based secure scheme for cognitive radio networks. In the proposed scheme, the secondary users harvest energy from the radio-frequency signals to securely transmit the secondary privacy information with the NOMA technique. Unlike the conventional ideal linear energy harvesting, we employ the practical nonlinear energy harvesting model for energy harvesting. To implement the proposed scheme, the energy transmitter first broadcasts radiofrequency signals to power the secondary users. Then, the secondary users employ the NOMA technique to transmit the uplink privacy information which is threatened by the eavesdropper. Considering two scenarios: two secondary users and more than two secondary users, we first provide comprehensive analysis of the secondary secrecy performances, and derive the closed-form expressions of the secrecy outage probability for both scenarios. Following the above analysis, we develop the optimization problems to optimally allocate the time slot and the secondary transmit power such that the minimum secrecy energy efficiency is maximized under constraints of the transmission security and reliability requirements. A two stages algorithm is proposed to efficiently solve the above optimization problems. Numerical results are presented to verify the analysis in terms of the secrecy rate and secrecy energy efficiency.

In this paper, we propose a mobile edge computing (MEC)-enabled unmanned aerial vehicle (UAV)-assisted vehicular ad hoc network (VANET) architecture, based on which a number of vehicles are served by UAVs equipped with computation resource. Each vehicle has to offload its computing tasks to the proper MEC server on the UAV due to the limited computation ability. To counter the problems above, we first model and analyze the transmission model and the security assurance model from the vehicle to the MEC server on UAV, and the task computation model of the local vehicle and the edge UAV. Then, the vehicle offloading problem is formulated as a multi-objective optimization problem by jointly considering the task offloading, the resource allocation, and the security assurance. For tackling this hard problem, we decouple the multi-objective optimization problem as two subproblems and propose an efficient iterative algorithm to jointly make the MEC selection decision based on the criteria of load balancing and optimize the offloading ratio and the computation resource according to the Lagrangian dual decomposition. Finally, the simulation results demonstrate that our proposed scheme achieves significant performance superiority compared with other schemes in terms of the successful task processing ratio and the task processing delay.

Providing reliable and flexible emergency communications for the Internet of Vehicles (IoV) is challenging in post-disaster scenarios, especially when communications infrastructures are unavailable or seriously damaged. Under such circumstances, it is highly demanded to deploy the air base station (ABS) to restore connectivity in disaster areas. Although the ABS can offer improved performance, the massive access of communications devices and the rising demand for many emergency-related services will bring new challenges to the ABS-aided IoV. In this paper, we propose a vehicle-to-infrastructure (V2I) and vehicle-to-vehicle (V2V) collaboration framework to support emergency communications. Specifically, we incorporate non-orthogonal multiple access (NOMA) into the ABS-aided IoV. By using the successive interference cancellation (SIC) technique, V2I and V2V links can operate in four spectrum reuse modes, which are the extension of the conventional underlaying reuse mode. To fully exploit the advantages of the NOMA enhanced collaboration framework, we formulate a total power consumption minimization problem by jointly considering the mode selection, power control, and the channel state information (CSI) latency. The formulated problem is constrained by the reliability and rate requirements, and the decoding threshold of the SIC technique. Due to the NP-hard characteristics of the formulated problem, we decouple it first, and then adopt the graphical method to derive the analytical solution of optimal power control policies. Afterwards, we can get every feasible spectrum reuse mode. Among the feasible modes, we select the mode with minimum power consumption as the optimal mode. Finally, simulation results demonstrate that our proposed algorithm outperforms the current works in term of the total power consumption, e.g., by adopting the ABS and the NOMA technology, the total power consumption can be reduced by 22.3% and 40.9%, respectively.

This paper proposes an active aerial reconfigurable intelligent surface (ARIS) assisted secure communication framework by integrating sensing and positioning against a mobile eavesdropper. In the proposed scheme, the base station (BS) beamforms the private information to the legitimate user and jams the eavesdropper with artificial noise (AN), while reconfiguring the phases and amplitudes of the passive signal by the active ARIS for promoting secure communications. To acquire the channel state information of the time-vary wiretap channel, the BS tracks the position of the eavesdropper by exploiting the reflected AN. Based on the tracked position of the eavesdropper in the previous time slot, we propose a secure communication scheme that aims to maximize the secrecy rate in the current time slot. This scheme is assisted by the ARIS through jointly optimizing the passive beamforming of the privacy information and AN, the reflection matrix of the ARIS, and the position of the ARIS. In the case of this non-convex quandary with highly coupled variables, we opt to disassemble it into three constituent subproblems and design an alternating optimization framework, where the optimal power beamforming at the BS is derived using a successive convex approximation method and semi-positive definite relaxation technique, the reconfigurable coefficient of the ARIS is optimized using the majorization-minimization algorithm, and the optimal position of the ARIS using the three-dimensional network is obtained by the deep deterministic policy gradient algorithm. Simulation results demonstrate the superior performance of the proposed scheme in the context of the secrecy rate when compared with benchmark schemes. By adopting the active beamforming and positioning technique, the secrecy rate can be increased by 38.3% and 10.8%, respectively.